# A. Kaveh

45.82

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713

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Introduction

**Skills and Expertise**

Finite Element AnalysisStructural AnalysisModeling and SimulationNumerical ModelingOptimizationNumerical AnalysisEngineering, Applied and Computational MathematicsAlgorithmsMathematical ModellingMathematical AnalysisSimulationConstruction MaterialsModelingApplied MathematicsFinite Element MethodComputational MechanicsTopologyMathematical ProgrammingAnalysisHeuristicsDiscrete MathematicsNumerical MathematicsArtificial Neural NetworksGraph ΤheoryCombinatoricsGroup TheoryAlgebraNeural NetworksCombinatorial OptimizationStructural EngineeringFinite DifferenceAlgorithm DevelopmentGenetic AlgorithmSteelPartial Differential EquationsGraphsReinforced ConcreteNumbersAlgorithm AnalysisOptimization MethodsComputationDiscrete OptimizationParticle Swarm OptimizationBackpropagationCalculationsOptimization AlgorithmsApplied AnalysisNetwork OptimizationMatricesNumerical OptimizationLinear AlgebraAlgorithm DesignMatrixAnt Colony OptimizationMetaheuristicLinear SystemsOptimization (Mathematical Programming)Theory of ComputationGraph AlgorithmsBuilding CodesDomain DecompositionMetaheuristic AlgorithmEcholocationMathematical ConceptsMatrix structural analysis

Research Experience

Apr 2015 - Aug 2015

- Institute of Mechanics of Materials and Structures
- Vienna, Austria

Position

- Guest professor

Description

- In different intervals I was guest professor at TU-Wien

Jan 2002 - Apr 2014

Current institution

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Network

Co-authors

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Following

Projects

Projects (9)

Project

Research

Research Item (713)

- Jul 2018

Steel pitched roof frames with the tapper fabricated members is the common solution for a wide range of industrial structures. In the present research, design optimization of the steel member sections is performed by different apex heights and tapered lengths for steel pitched roof frames. The effective variable definition has helped to reduce the variable domain and ignore the unwanted part of the bounds before starting the optimization process. Nine metaheuristic algorithms are used for the optimization. Results show that selecting apex height and tapered length can change optimum weight of structure by 10%. Additionally, performance of the considered metaheuristic algorithms is compared for this type of frame structures.

- Jun 2018

In this paper, a finite element model based on geometrical nonlinear analysis of large-scale double-layer domes and suspen-domes with pinned and rigid connections is presented. An optimal geometry and sizing design are performed using the enhanced colliding bodies optimization (ECBO) method. The length of the strut, the cable initial strain, the cross-sectional areas of the cables and steel elements, and height of domes are considered as design variables and the volume of each dome is taken as the objective function. A simple approach is defined to determine the configurations of the dome structures. This approach includes calculating the joint coordinates and formation of steel elements and cables. Numerical results show the robustness of ECBO algorithm. The efficiency of Lamella suspen-dome with pin-joint and rigid-joint connections is then explored and compared with double-layer Lamella dome to investigate the performance of these systems under dead and snow loading condition. Optimization process is performed via ECBO algorithm to demonstrate the effectiveness and robustness of the ECBO in finding optimal designs for different systems of domes.

- Jun 2018

In this paper, a set of recently developed interactive constitutive laws for reinforced concrete is revised. The main improvement is considering the effect of crack inclination angle on the tension-stiffening phenomenon. The influence of reinforcing bars on tensile behavior of concrete after cracking is included as a function of their angle with respect to the tension cracks. To calibrate the parameters of the model, the harmony search meta-heuristic algorithm is used. Furthermore, the experimental load–deformation curves of 13 membrane-reinforced concrete elements, with a wide range of specifications, are compared to the predicted curves obtained by the proposed method.

- May 2018

This paper presents a finite element method for the analysis of scissor-link foldable structures. These structures are capable of deforming from compact form to expanded form, and vice versa. Due to their complex mechanism, it is difficult and time-consuming to simulate foldable structures in analysis softwares, while the proposed method of this paper makes it easy to perform the analysis in a simple manner. In addition, this paper uses two different multi-objective meta-heuristic algorithms, NSGAII and MOCBO, to perform optimum design of foldable structures. The purpose is to find designs that result in minimum weight and minimum volume of the structures satisfying all the constraints consisting of maximum stress, elements buckling, and permissible displacement.

- May 2018

The present study is concerned with optimal design of steel frames under seismic loads based on response spectra. Four metaheuristic algorithms, consisting of colliding-bodies optimization (CBO), enhanced colliding-bodies optimization (ECBO), vibrating particles system (VPS), and a hybrid algorithm based on VPS, multidesign variable configurations (MDVC) cascade optimization, and upper-bound strategy (UBS), are used in order to perform the optimal design of three-dimensional (3D) irregular steel frames. Frame members are chosen from an available set of steel sections for producing practically acceptable designs according to a current design standard. The numerical results of the investigated design examples illustrate the advantages of the hybrid algorithm (MDVC-UVPS) in terms of the optimality of the final solution and the speed of convergence.

- Apr 2018

In this paper three well-known metaheuristic algorithms comprising of Colliding Bodies Optimization, Enhanced Colliding Bodies Optimization, and Particle Swarm Optimization are employed for size and performance optimization of steel plate shear wall systems. Low seismic and high seismic optimal designs of these systems are performed according to the provisions of AISC 360 and AISC 341. In one part of the low seismic example, a moment frame and Steel Plate Shear Wall (SPW) strength are compared. Performance optimization of the Special Plate Shear Wall (SPSW) for size optimized system is one of the objectives of the high seismic example. Finally, base shear sensitivity analysis on optimal high seismic design of SPSW and size optimization of a 6-story to a 12-story SPSW are performed to have a comprehensive view on the optimal design of steel plate shear walls.

- Apr 2018
- Meta-heuristic Algorithms for Optimal Design of Real-Size Structures

Steel buildings are preferred in residential as well as commercial buildings because of being super-quick to build at site, as a great deal of work can be prefabricated at the factory. Moreover, these structures are flexible, which makes them quite suitable structures for resisting dynamic forces such as earthquake loads. Design of frame structures necessitates the selection of steel sections for its columns and beams from a standard steel section tables such that the frame satisfies the serviceability and strength requirements specified by the code of practice while the economy is taken into account in the overall or material cost of the frame. The contribution of this chapter is concerned with optimization of steel frames under seismic loads based on response spectral. Frame members are selected from available set of steel sections for producing practically acceptable designs according to Load and Resistance Factor Design-American Institute of Steel Construction (LRFD-AISC) specification. Three irregular steel frame problems are considered to evaluate the performance of the CBO, ECBO, VPS and MDVC-UVPS algorithms.

- Apr 2018
- Meta-heuristic Algorithms for Optimal Design of Real-Size Structures

Double-layer grids belong to the category of space structures and consist of two planar networks of members forming the top and bottom layers parallel to each other and interconnected by vertical and inclined web members. Double layer grids are characterized by ball joints with no moment or torsional resistance; therefore, all members can only resist tension or compression. In the last decades, a number of meta-heuristic algorithms have been developed and used for structural optimization problems. Double-layer grids have a great number of structural elements, and therefore optimization techniques can be rewardingly employed to achieve economic and efficient designs of them. Here, five different types of double-layer grids are studied and optimized utilizing the colliding bodies optimization (CBO), enhanced colliding bodies optimization (ECBO), vibrating particles system (VPS), and a hybrid algorithm called MDVC-UVPS. The cross-section areas of the grid elements are considered as discrete design variables and all of them are selected from a list of tube sections available in AISC-LRFD. Strength, stability, and displacement constraints are considered for each example.

- Apr 2018
- Meta-heuristic Algorithms for Optimal Design of Real-Size Structures

Lattice towers are used for power lines of all voltages, and are the most common type for high-voltage transmission lines. The design optimization of these structures has always been a difficult task due to a large number of design variables. Some studies have already been performed in the context of optimization of transmission line tower structures. In this chapter, the efficiency of colliding bodies optimization (CBO), enhanced colliding bodies optimization (ECBO), vibrating particles system (VPS), and a hybrid algorithm called MDVC-UVPS are investigated in optimum design of three latticed steel towers. The procedure considers discrete values of cross-sectional areas.

- Apr 2018
- Meta-heuristic Algorithms for Optimal Design of Real-Size Structures

The main features and rules of the optimization algorithms utilized in this book are explained in this chapter. These algorithms consist of Colliding Bodies Optimization (CBO), Enhanced Colliding Bodies Optimization (ECBO), Vibrating Particles System (VPS) and a hybrid algorithm called MDVC-UVPS. All of the algorithms considered here are recently developed and are multi-agent meta-heuristic methods. These algorithms start with a set of randomly selected candidate solutions of the optimization problem and according to a series of simple rules, mainly inspired by the nature, the existing solutions are perturbed iteratively in order to improve their cost function values.

- Apr 2018
- Meta-heuristic Algorithms for Optimal Design of Real-Size Structures

Sizing optimization of truss and frame structures are frequent structural design problems that are subjected to various constraints such as displacements, stress, buckling, and natural frequencies. A great number of papers has been published in literature, where different meta-heuristic search algorithms have been applied to this class of problems. The aim of this chapter is to examine the ability of the CBO, ECBO and VPS which have been utilized in the next chapters for comparison with MDVC-UVPS. The results of well-known state-of-the-art meta-heuristics are also provided and compared here.

- Apr 2018
- Meta-heuristic Algorithms for Optimal Design of Real-Size Structures

A truss is a two or three-dimensional structure composed of linear members connected at nodes to sustain concentrated loads with the members being subjected to tension or compression. Optimum design problems of steel trusses are known as benchmarks in the field of structural optimization due to the presence of many design variables, large search spaces and multiple constraints. In this chapter sizing optimization of large-scale tower trusses is studied. Steel truss members are adopted from a predetermined list of available sections; therefore, a discrete optimization is performed in order to obtain the optimum or a near optimum solution. These types of structures are typically considered as high-rise and large-scale structures composed of several hundred elements. These towers have important applications in telecommunication and broadcasting industries.

- Apr 2018
- Meta-heuristic Algorithms for Optimal Design of Real-Size Structures

Domes are one of the oldest and well-established structural forms and have been used in architecture since the earliest times. These structures are of special interest to engineers as they enclose large spaces with small surfaces and have proven to be very economical in terms of consumption of constructional materials. The main aim of this chapter is frequency constraint optimization of dome truss structures; however, all the domes are also optimized considering strength, stability, and displacement constraints. Structural optimization considering natural frequency constraints is believed to represent nonlinear and non-convex search spaces with several local optima. In this class of problems, large generalized eigenproblems should be solved in order to find the natural frequencies of the structure. The size of the structure affects the dimensions of the matrices involved and thus the required computational time and effort. On the other hand, as the number of optimization variables increases, more and more structural analyses are needed to be performed in order to reach a near-optimal solution.

- Apr 2018
- Meta-heuristic Algorithms for Optimal Design of Real-Size Structures

Barrel vaults are given different names depending on the way their surface is formed. The earlier types of barrel vaults were constructed as single-layer structures. Nowadays, with the increase of the spans, double-layer systems are often preferred. While the members of single-layer barrel vaults are mainly under the action of flexural moments, those of double-layer barrel vaults are almost exclusively under the action of axial forces and the elimination of bending moments leads to a full utilization of strength of all the elements. Double layer barrel vaults are generally statically indeterminate. In such systems, due to the rigidity, the risk of instability can almost be eliminated. The use of this type of barrel vaults enhances the stiffness of the vault structure and provides structural systems of great potential, capable of having spans in excess of 100 m. In this chapter, three double-layer barrel roof structures are optimized to investigate the performance of the CBO, ECBO, VPS and MDVC-UVPS meta-heuristic algorithms. The structures are subjected to stress, stability and displacement limitations according to the provisions of AISC-ASD. The design variables are the cross-sectional areas of the bar elements which are selected from a list of steel pipe sections.

- Apr 2018

Location optimization of tower crane as an expensive equipment in the construction projects has an important effect on material transportation costs. Due to the construction site conditions, there are several tower crane location optimization models. Appropriate location of tower cranes for material supply and engineering demands is a combinatorial optimization problem within the tower crane layout problem that is difficult to resolve. Meta-heuristics are popular and useful techniques to resolve complex optimization problems. In this paper, the performance of the Particle Swarm Optimization (PSO) and four newly developed meta-heuristic algorithms Colliding Bodies Optimization (CBO), Enhanced Colliding Bodies Optimization (ECBO), Vibrating Particles System (VPS), and Enhanced Vibrating Particles System (EVPS) are compared in terms of their effectiveness in resolving a practical Tower Crane Layout (TCL) problem. Results show that ECBO performs better than other three methods in both cases.

- Apr 2018

Construction site layout planning can be considered as an effort to place different temporary facilities in available site locations such that multiple objectives are satisfied as much as possible. With the extension of high-rise building construction and construction activities besides the lack of available spaces in construction sites, proper utilization of this resource has been highlighted because of its significant positive influences on direct cost, safety, and security of the site which consequently affects the total cost and schedule of the project. Thus the construction site layout planning is considered as one of the essential and important phases in construction projects. Site layout planning problem is an NP-Hard problem from the viewpoint of complexity. In this research, two prominent meta-heuristic algorithms, namely Charged System Search (CSS) and Magnetic Charged System Search (MCSS) are utilized to optimize the site layout planning problem. The obtained results of implementing these two algorithms for two different types of site space modeling are compared with the results of the Particle Swarm Optimization (PSO) algorithm and also those of the previous studies. The results illustrate the capability of the CSS and MCSS algorithms in solving the present problem.

- Apr 2018

This article presents a new population-based optimization algorithm to solve the multi-objective optimization problems of truss structures. This method is based on the recently developed single-solution algorithm proposed by the present authors, so called colliding bodies optimization (CBO), with each agent solution being considered as an object or body with mass. In the proposed multi-objective colliding bodies optimization (MOCBO) algorithm, the collision theory strategy as the search process is utilized and the Maximin fitness procedure is incorporated to the CBO for sorting the agents. A series of well-known test functions with different characteristics and number of objective functions are studied. In order to measure the accuracy and efficiency of the proposed algorithm, its results are compared to those of the previous methods available in the literature, such as SPEA2, NSGA-II and MOPSO algorithms. Thereafter, two truss structural examples considering bi-objective functions are optimized. The performance of the proposed algorithm is more accurate and requires a lower computational cost than the other considered algorithms. In addition, the present methodology uses simple formulation and does not require internal parameter tuning.

- Mar 2018

Colliding bodies optimization (CBO) is a recently developed population-based metaheuristic algorithm that mimics the collision between two bodies, where the momentum conservation law is utilized to determine the new positions of the agents in the search space. To overcome some deficiencies in the CBO like slow convergence and getting trapped in local minima, an enhanced version of the algorithm, ECBO, is proposed. One of the efficient techniques to improve the performances of the metaheuristic algorithms is adding chaos to their structure. In this paper, chaos is incorporated into the ECBO through three types of embeddings and ten chaotic maps. Proposing different chaotic versions, finding the best version among chaotic versions and improving the efficiency of the standard CBO and ECBO are the main achievements of this study. The results of examining some mathematical and engineering problems show how some chaotic ECBO variants can enhance the performance of the standard ECBO

- Mar 2018

Determining the optimum placement of braces in steel frames has always been one of the most challenging issues in structural engineering. In this paper, the size and placement of the X-braces in planar frame structures is determined in a way that the total weight of the braced frames becomes minimum, while satisfying the design requirements and constraints. Variables of the optimization contain the cross sections for beams, columns, and X-braces as well as the placement of these braces in the frames. Attempt has also been made to consider all the constraints of an actual design problem. One of the other objectives of this study is to investigate the effect of including or excluding some of the constraints affecting the optimization of the planar frame design. For this purpose, the Colliding Bodies Optimization (CBO) and CBO-MDM algorithms have been utilized. Modified Dolphin Monitoring (MDM) operator is recently developed for improving the performance of the metaheuristic algorithms. Here, this operator is utilized to enhance the performance of the CBO algorithm to optimize the weight of the frames. For additional comparison of the results, the particle swarm optimization (PSO) algorithm and imperialist competitive algorithm (ICA) are used.

- Mar 2018

Simplified Dolphin Echolocation (SDE) algorithm is a recently developed meta-heuristic algorithm. This algorithm is an improved and simplified version of the Dolphin Echolocation Optimization (DEO) method, based on the baiting behavior of the dolphins. The main advantage of the SDE algorithm is that it needs no empirical parameter. In this paper, the SDE algorithm is applied for optimization of three well-studied frame structures. The designs are then compared with those of other meta-heuristic methods from the literature. Numerical results show the efficiency of the SDE algorithm and its competitive ability with other well-established meta-heuristics methods.

- Mar 2018

Construction site layout planning can be considered as an effort to place different temporary facilities in available site locations such that multiple objectives are satisfied as much as possible. With the extension of high-rise building construction and construction activities besides the lack of available spaces in construction sites, proper utilization of this resource has been highlighted because of its significant positive influences on direct cost, safety, and security of the site which consequently affects the total cost and schedule of the project. Thus the construction site layout planning is considered as one of the essential and important phases in construction projects. Site layout planning problem is an NP-Hard problem from the viewpoint of complexity. In this research, two prominent meta-heuristic algorithms, namely Charged System Search (CSS) and Magnetic Charged System Search (MCSS) are utilized to optimize the site layout planning problem. The obtained results of implementing these two algorithms for two different types of site space modeling are compared with the results of the Particle Swarm Optimization (PSO) algorithm and also those of the previous studies. The results illustrate the capability of the CSS and MCSS algorithms in solving the present problem. Keywords construction site layout planning, meta-heuristic optimization algorithms, charged system search, magnetic charged system search, particle swarm optimization.

- Feb 2018

Thermal Exchange Optimization (TEO) is a newly developed algorithm which mimics the thermal exchange between a solid object and its surrounding fluid. In this paper, an improved version of the TEO is developed to fix the shortcomings of the standard version. To demonstrate the viability of the new algorithm, the CEC 2016’s single objective problems are considered along with the discrete size optimization of benchmark skeletal structures. Problem specific constraints are handled using a fly-back mechanism. The results show the validity of the improved TEO method compared to its standard version and a number of well-known algorithms.

- Feb 2018

In this paper, the Colliding Bodies Optimization (CBO), Enhanced Colliding Bodies Optimization (ECBO) and Vibrating Particles System (VPS) algorithms and the force method are used for the simultaneous analysis and design of truss structures. The presented technique is applied to the design and analysis of some planer and spatial trusses. An efficient method is introduced using the CBO, ECBO and VPS to design trusses having members of prescribed stress ratios. Finally, the minimum weight design of truss structures is formulated using the CBO, ECBO and VPS algorithms and applied to some benchmark problems from literature. These problems have been designed by using displacement method as analyzer, and here these are solved for the first time using the force method. The accuracy and efficiency of the presented method is examined by comparing the resulting design parameters and structural weight with those of other existing methods.

- Feb 2018

In this article, the newly developed optimization method, so-called the Lion Pride Optimization Algorithm (LPOA), is applied to optimal design of double-layer space barrel vaults. In order to demonstrate the performance of the LPOA, three large-scale benchmark optimization design problems of double-layer barrel vaults are optimized and the results are compared with those of some metaheuristics from literature. The second aim of this article is to solve these examples using three other robust metaheuristic algorithms, namely Artificial Bee Colony (ABC), Cuckoo Search (CS), and Particle Swarm Optimization (PSO). A comparative study of these algorithms shows the suitability of the LPOA for solving real-world practical spatial truss structures.

- Jan 2018

The contributions in this book discuss large-scale problems like the optimal design of domes, antennas, transmission line towers, barrel vaults and steel frames with different types of limitations such as strength, buckling, displacement and natural frequencies. The authors use a set of definite algorithms for the optimization of all types of structures. They also add a new enhanced version of VPS and information about configuration processes to all chapters. Domes are of special interest to engineers as they enclose a maximum amount of space with a minimum surface and have proven to be very economical in terms of consumption of constructional materials. Antennas and transmission line towers are the one of the most popular structure since these steel lattice towers are inexpensive, strong, light and wind resistant. Architects and engineers choose barrel vaults as viable and often highly suitable forms for covering not only low-cost industrial buildings, warehouses, large-span hangars, indoor sports stadiums, but also large cultural and leisure centers. Steel buildings are preferred in residential as well as commercial buildings due to their high strength and ductility particularly in regions which are prone to earthquakes.

- Dec 2017

This paper presents the application of the biogeography-based optimization (BBO) and some of its variants in the optimization of stacking sequence of laminated composites. Harmony search is also implemented to compare its results with those of the BBO. The optimization objective is to maximize the buckling load of a symmetric and balanced laminated plate. Four laminated composites with different loadings and dimensions are studied, and the statistical comparison of the obtained configurations and buckling load capacities shows the high capability of the BBO with quadratic migration model in terms of robustness and global search.

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

High number of design variables, large size of the search space, and control of a great number of design constraints are major preventive factors in performing optimum design of real-world structures in a reasonable time. This chapter presents an accurate and efficient technique for optimal design of truss towers with large number of design variables to illustrate its applicability to optimum design of practical structures [1].

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

This chapter deals with the optimal design of double-layer Lamella domes, Suspen-Domes, and single-layer domes with relatively long spans including nonlinear structural behavior [1]. In recent years, much progress has been made in the optimal design of space structures by focusing on their linear behavior, neglecting nonlinearities which can result in uneconomic designs. In this study, geometric nonlinearity optimization is taken into account for the abovementioned domes. There are two main steps involved in the optimization of structural problems: analysis and design. In this chapter, OPENSEES [2] is employed for analysis, and enhanced colliding body is utilized in the design phase. All of the required programs for the optimization phase are coded in MATLAB [3]. The design variables include cross-sectional areas of the structural elements, the height of dome, the initial strain of cables, and the cross sections of cables in the Suspen-Dome. In order to illustrate the efficiency of the proposed methodology, three numerical examples including optimization of a single-layer dome with rigid-jointed, suspen-dome, and double-layer domes with 12 rings subjected to dead and snow loading are presented. The main contribution of the chapter is to utilize an efficient metaheuristic algorithm for optimization of domes. Optimal design of structures is usually achieved by considering the design variables to find an objective function which is the minimum weight while all of the design constraints are satisfied.

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

In this chapter the recently developed physically inspired non-gradient algorithm is employed for structural optimization with frequency constraints. The algorithm being called vibrating particles system (VPS) mimics the free vibration of single degree of freedom systems with viscous damping. Truss optimization with frequency constraints is believed to represent nonlinear and non-convex search spaces with several local optima and therefore is suitable for examining the capabilities of the new algorithms. A set of five truss design problems are considered for evaluating the VPS in this article. The numerical results demonstrate the efficiency and robustness of the new method (Kaveh and Ilchi Ghazaan [1]).

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

The whale optimization algorithm (WOA) is a recently developed swarm-based optimization algorithm inspired by the hunting behavior of humpback whales. This study attempts to enhance the original formulation of the WOA in order to improve solution accuracy, reliability, and convergence speed. The new method, called enhanced whale optimization algorithm (EWOA), is tested in the sizing optimization of skeletal structures. In this chapter, EWOA is also compared with WOA and other metaheuristic methods developed in the literature using four skeletal structure optimization problems. Numerical results compare the efficiency of the WOA and EWOA with the latter algorithm being superior to the standard implementation [1].

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

Structural optimization involves a large number of structural analyses. When optimizing large structures, these analyses require a considerable amount of computational time and effort. However, there are specific types of structure for which the results of the analysis can be achieved in a much simpler and quicker way due to their special repetitive patterns. In this chapter, frequency constraint optimization of cyclically repeated space trusses is considered. An efficient technique is used to decompose the large initial eigenproblem into several smaller ones and thus to decrease the required computational time significantly (Kaveh and Zolghadr [1]).

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

In this chapter a simple and robust approach is presented for spectral matching of ground motions utilizing the wavelet transform and an improved metaheuristic optimization technique. For this purpose, wavelet transform is used to decompose the original ground motions to several levels, where each level covers a special range of frequency, and then each level is multiplied by a variable. Subsequently, the enhanced colliding bodies optimization (ECBO) technique is employed to calculate the variables such that the error between the response and target spectra is minimized. The application of the proposed method is illustrated through modifying 12 sets of ground motions [1].

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

Tubular steel monopole structures are widely used for supporting antennas in telecommunication industries. This research presents two recently developed metaheuristic algorithms, so-called colliding bodies optimization (CBO) and its enhanced version (ECBO), for size optimization of monopole steel structures. The optimal design procedure aims to obtain minimum weight of monopole structures subjected to the TIA-EIA222F specification. Two monopole structure examples are examined to verify the suitability of the design procedure and to demonstrate the effectiveness and robustness of the CBO and ECBO in creating optimal design for this problem. The outcomes of the ECBO are also compared to those of the standard CBO to illustrate the importance of the enhancement of the CBO algorithm [1].

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

Barrel vault is one of the oldest architectural forms, used since antiquity. The brick architecture of the Orient or the masonry construction of the Romans provides numerous examples of the structural use of barrel vaults. The industrial and technological developments which have taken place during the last three decades have had a far-reaching effect upon contemporary architecture and modern engineering. New building techniques, new constructional materials, and new structural forms have been introduced all over the world. The architectural search for new structural forms has resulted in the widespread use of three-dimensional structures. The evolution of effective computer techniques of analysis is undoubtedly one of the reasons for the truly phenomenal acceptance of space structures. During recent years, architects and engineers have rediscovered the advantages of barrel vaults as viable and often highly suitable forms for covering not only low-cost industrial buildings, warehouses, large-span hangars, and indoor sports stadium but also large cultural and leisure centers. The impact of industrialization on prefabricated barrel vaults has proved to be the most significant factor leading to lower costs for these structures. A barrel vault consists of one or more layers of elements that are arched in one direction [1]. Barrel vaults are given different names depending on the way their surface is formed. The earlier types of barrel vaults were constructed as single-layer structures [2–4]. Nowadays, with increase of the spans, double-layer systems are often preferred. Whereas the single-layer barrel vaults are mainly under the action of flexural moments, the component members of double-layer barrel vaults are almost exclusively under the action of axial forces; the elimination of bending moments leads to a full utilization of strength of all the elements. Formex algebra is a mathematical system that provides a convenient medium for configuration processing. The concepts are general and can be used in many fields. In particular, the ideas may be employed for generation of information about various aspects of structural systems such as element connectivity, nodal coordinates, details of loadings, joint numbers, and support arrangements. The information generated may be used for various purposes, such as graphic visualization or input data for structural analysis. Double-layer barrel vaults have great number of structural elements, and utilizing optimization techniques has considerable influence on the economy.

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

This chapter investigates discrete design optimization of reinforcement concrete frames using the recently developed metaheuristic called Enhanced Colliding Bodies Optimization (ECBO) and the Non-dominated Sorting Enhanced Colliding Bodies Optimization (NSECBO) algorithm. The objective function of algorithms consists of construction material costs of reinforced concrete structural elements and carbon dioxide (\( {\mathrm{CO}}_2 \)) emissions through different phases of a building life cycle that meets the standards and requirements of the American Concrete Institute’s Building Code. The proposed method uses predetermined section database (DB) for design variables that are taken as the area of steel and the geometry of cross sections of beams and columns. A number of benchmark test problems are optimized to verify the good performance of this methodology. The use of ECBO algorithm for designing reinforced concrete frames indicates an improvement in the computational efficiency over the designs performed by Big Bang–Big Crunch (BB–BC) algorithm. The analysis also reveals that the two objective functions are quite relevant and designs focused on mitigating \( {\mathrm{CO}}_2 \) emissions could be achieved at an acceptable cost increment in practice. Pareto results of the NSECBO algorithm indicate that both objective yield similar solutions [1].

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

Space structures have become popular not only because of their topological attractiveness and greater reserves of strength compared to conventional structures but also their easy and fast construction. Double-layer grids are ideally suited for covering exhibition pavilions, assembly halls, swimming pools, hangars, churches, bridge decks, and many types of industrial buildings in which large unobstructed areas are required. Double-layer grids have been built successfully at a lower cost than equivalent conventional systems, providing at the same time additional advantages, such as greater rigidity, erection simplicity, and possibility of covering larger areas.

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

Decks, interior beams, edge beams, and girders are parts of a steel floor system. If the deck is optimized without considering beam optimization, finding the best result is simple. However, a deck with a higher cost may increase the composite action of the beams and decrease the beam cost, thus reducing the total expense. Also, a different number of floor divisions can improve the total floor cost. Increasing beam capacity by using castellated beams is another efficient cost-saving method. In this study, floor optimization is performed and these three issues are discussed. Floor division number and deck sections are some of the variables. Also, for each beam, profile section of the beam, beam-cutting depth, cutting angle, spacing between holes, and number of filled holes at the ends of castellated beams are other variables. Constraints include the application of stress, stability, deflection, and vibration limitations according to the load and resistance factor (LRFD) design. The objective function is the total cost of the floor consisting of the steel profile, cutting and welding, concrete, steel deck, shear stud, and construction costs. Optimization is performed by enhanced colliding bodies optimization (ECBO). Results show that using castellated beams, selecting a deck with a higher price and considering the different number of floor divisions can decrease the total cost of the floor (Kaveh and Ghafari [1]).

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

In this chapter, the tug of war algorithm is applied to optimal design of castellated beams. Two common types of laterally supported castellated beams are considered as design problems: beams with hexagonal openings and beams with circular openings. Here, castellated beams have been studied for two cases: beams without filled holes and beams with end-filled holes. Also, tug of war optimization algorithm is utilized for obtaining the solution of these design problems. For this purpose, the cost is taken as the objective function, and some benchmark problems are solved from literature (Kaveh and Shokohi [1]).

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

The increasing use of braced barrel vaults as a lightweight space structure is very common. Optimizing barrel vaults, therefore, can prove a worthwhile venture [1]. Metaheuristic algorithms explore the feasible region of the search space based on both randomization and some specified rules through a group of search agents. Nature-inspired phenomena are commonly used as a basis for the rules employed by these agents [2].

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

Composite steel–concrete box girders are frequently used in bridge construction for their economic and structural advantages. An integrated metaheuristic based optimization procedure is proposed for discrete size optimization of straight multi-span steel-box girders with the objective of minimizing the self-weight of the girder. The selected metaheuristic algorithm is the cuckoo search (CS) algorithm. The optimum design of a box girder is characterized by geometry, serviceability, and ultimate limit states specified by the American Association of State Highway and Transportation Officials (AASHTO). Size optimization of a practical design example investigates the efficiency of this optimization approach and leads to around 15 % of saving in material (Kaveh and Shokohi [1]).

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

In this chapter, two recently developed metaheuristic algorithms, so-called CBO and ECBO, are employed for construction site layout planning. Results show that both of these algorithms have the capability of solving this kind of problem. Two case studies are presented to show the applicability and performance of the utilized methods [1].

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

It is well known that damaged structural members may alter the behavior of the structures considerably. Careful observation of these changes has often been viewed as a means to identify and assess the location and severity of damages in structures. Among the responses of a structure, natural frequencies and natural modes are both relatively easy to obtain and independent from external excitation and, therefore, can be used as a measure of the structural behavior before and after an extreme event which might have led to damage in the structure. This chapter applies charged system search algorithm to the problem of damage detection using vibration data. The objective is to identify the location and extent of multi-damage in a structure. Both natural frequencies and mode shapes are used to form the required objective function. To moderate the effect of noise on measured data, a penalty approach is applied. A variety of numerical examples including beams, frames, and trusses are examined. The results show that the present methodology can reliably identify damage scenarios using noisy measurements and incomplete data [1].

- Dec 2017
- Applications of Metaheuristic Optimization Algorithms in Civil Engineering

In this chapter three recently developed metaheuristic optimization algorithms, known as colliding bodies optimization (CBO), enhanced colliding bodies optimization (ECBO), and tug of war optimization (TWO), are utilized for optimum nodal ordering to reduce bandwidth, profile, and wavefront of sparse matrices. The bandwidth, profile, and wavefront of some graph matrices, which have equivalent pattern to structural matrices, are minimized using these methods. Comparison of the achieved results with those of some existing approaches shows the robustness of these three new metaheuristic algorithms for bandwidth, profile, and wavefront optimization [1].

- Dec 2017

Much has been made of the parallels between engineering and art, and yet a unique economy of parts and adherence to a plethora of constraints from cost to market trends, from maintainability to robustness, and from project schedules safely distinguish engineering design from the arts and engineering projects from artworks. At the heart of this distinction lies the concept of “optimization” – the science of choosing design variable values within given constraints such that a function, e.g., total system cost, is minimized or, e.g., overall system reliability is maximized.

- Dec 2017

Considering the size and dimension of offshore wind turbine structures, structural optimization of such structures, notwithstanding being outstandingly fruitful, is a tedious task. Nonetheless, in this paper, a metaheuristic algorithm named as colliding bodies optimization is employed when investigating the optimal design of jacket supporting structures for offshore wind turbines. The OC4 reference jacket is considered as the case study, validating the outcomes of this research. To do so, MATLAB is utilized in modeling the structure. The structural optimization is then performed when both ultimate limit state and frequency constraints are being considered. During the optimization process, the weight of the structure is approximately halved, and its first and second frequencies are kept within the considered soft–stiff range (0.21–0.32 Hz).

- Nov 2017

In this article, an improved grey wolf optimizer (IGWO) algorithm is developed for optimal design of truss structures. Grey wolf optimizer (GWO) is a recently proposed algorithm for optimization, which is herein improved to handle structural optimization in an efficient manner. In this work, performance of the GWO in structural optimization is also investigated. A few tunable parameters are defined to provide proper adaptability for the algorithm and to optimize the structures using fewer structural analyses, while obtaining finer solutions. Hence, in addition to reduce the computational efforts, better solutions are obtained as it is shown by several benchmark examples, where both GWO and IGWO are employed for the optimization. Mathematical functions as well as various design examples from small to large truss structures with different search spaces are examined to demonstrate the ability and efficiency of the present improved version in comparison to its standard version.

- Nov 2017

In this paper, some graph theoretical (topological) transformations are presented for simplifying certain problems involved in structural analysis. For each case, the main problem is stated and the proposed topological transformation is established. Once the required topological analysis is completed, a back transformation results in the solution for the main problem. The transformations studied here employ (i) models drawn on a lower dimensional space, (ii) models embedded on higher dimensional spaces and (iii) interchange models which have simpler connectivity properties than the corresponding original structural models. All these transformations are illustrated utilizing simple examples.

- Nov 2017

Structural optimization of offshore wind turbines is a tedious task due to the complexity of the problem. However, in this article, this problem is tackled using two meta-heuristic algorithms - Colliding Bodies Optimization (CBO) and its enhanced version (ECBO) - for a jacket supporting structure. The OC4 reference jacket is chosen as a case study to validate the methods utilized in this research. The jacket supporting structure is modeled in MATLAB and its optimal design is performed while both Ultimate Limit State (ULS) and frequency constraints are considered. In the present study, it is presumed that both wind and wave phenomena act in the same horizontal direction. As a result, all resultant forces and moments will act in-plane and the substructure can therefore be modeled in 2D space. Considerable weight reduction is obtained during the optimization process while fulfilling all constraints.

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

In this chapter an optimization method is presented based on a sociopolitically motivated strategy, called imperialist competitive algorithm (ICA). ICA is a multi-agent algorithm with each agent being a country, which is either a colony or an imperialist. These countries form some empires in the search space. Movement of the colonies toward their related imperialist, and imperialistic competition among the empires, forms the basis of the ICA. During these movements, the powerful imperialists are reinforced, and the weak ones are weakened and gradually collapsed, directing the algorithm toward optimum points. Here, ICA is utilized to optimize the skeletal structures which are based on [1, 2].

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

Over the last few decades, metaheuristic algorithms have been successfully used for solving complex global optimization problems in science and engineering. These methods, which are usually inspired by natural phenomena, do not require any gradient information of the involved functions and are generally independent of the quality of the starting points. As a result, metaheuristic optimizers are favorable choices when dealing with discontinuous, multimodal, non-smooth, and non-convex functions, especially when near-global optimum solutions are sought, and the intended computational effort is limited.

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

In this chapter a single-solution metaheuristic optimizer, namely, global sensitivity analysis-based (GSAB) algorithm [1], is presented that uses a basic set of mathematical techniques, namely, global sensitivity analysis. Sensitivity analysis (SA) studies the sensitivity of the model output with respect to its input parameters (Rahman [2]). This analysis is generally categorized as local SA and global SA techniques. While local SA studies the sensitivity of the model output about variations around a specific point, the global SA considers variations of the inputs within their entire feasibility space (Pianosi and Wagener [3], Zhai et al. [4]). One important feature of the GSA is factor prioritization (FP), which aims at ranking the inputs in terms of their relative contribution to output variability. The GSAB comprises of a single-solution optimization strategy and GSA-driven procedure, where the solution is guided by ranking the decision variables using the GSA approach, resulting in an efficient and rapid search. The proposed algorithm can be studied within the family of search algorithms such as the random search (RS) by Rastrigin [5], pattern search (PS) by Hooke and Jeeves [6], and vortex search (VS) by Dog and Ölmez [7] algorithms. In this method, similar to these algorithms, the search process is achieved in the specified boundaries. Contrary to these algorithms that use different functions for decreasing the search space, in the present method, the well-known GSA approach is employed to decrease the search boundaries. The minimization of an objective function is then performed by moving these search spaces into around the best global sample.

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

Colliding bodies optimization (CBO) was employed for size optimization of skeletal structures in Chap. 7. In this chapter, the enhanced colliding bodies optimization (ECBO) is presented that utilizes memory to save some historically best solution and uses a random procedure to avoid local optima which is also applied to skeletal structures [1, 2]. The capability of the CBO and ECBO is compared through three trusses and two frame structures. The design constraints of steel frames are imposed according to the provisions of LRFD–AISC.

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

Nature has provided inspiration for most of the man-made technologies. Scientists believe that dolphins are the second to humans in smartness and intelligence. Echolocation is the biological sonar used by dolphins and several kinds of other animals for navigation and hunting in various environments. This ability of dolphins is mimicked in this chapter to develop a new optimization method. There are different metaheuristic optimization methods, but in most of these algorithms, parameter tuning takes a considerable time of the user, persuading the scientists to develop ideas to improve these methods. Studies have shown that metaheuristic algorithms have certain governing rules and knowing these rules helps to get better results. Dolphin echolocation (DE) takes advantages of these rules and outperforms many existing optimization methods, while it has few parameters to be set. The new approach leads to excellent results with low computational efforts [1].

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

The Big Bang–Big Crunch (BB–BC) method developed by Erol and Eksin [1] consists of two phases: a Big Bang phase and a Big Crunch phase. In the Big Bang phase, candidate solutions are randomly distributed over the search space. Similar to other evolutionary algorithms, initial solutions are spread all over the search space in a uniform manner in the first Big Bang. Erol and Eksin [1] associated the random nature of the Big Bang to energy dissipation or the transformation from an ordered state (a convergent solution) to a disorder or chaos state (new set of solution candidates).

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

In this chapter, a metaheuristic method so-called cuckoo search (CS) algorithm is utilized to determine optimum design of structures for both discrete and continuous variables. This algorithm is recently developed by Yang [1] and Yang and Deb [2, 3], and it is based on the obligate brood parasitic behavior of some cuckoo species together with the Lévy flight behavior of some birds and fruit flies. The CS is a population-based optimization algorithm and, similar to many other metaheuristic algorithms, starts with a random initial population which is taken as host nests or eggs. The CS algorithm essentially works with three components: Selection of the best by keeping the best nests or solutionsReplacement of the host eggs with respect to the quality of the new solutions or cuckoo eggs produced based randomization via Lévy flights globally (exploration)Discovering of some cuckoo eggs by the host birds and replacing according to the quality of the local random walks (exploitation) [2]

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

Efficient metaheuristic optimization algorithms are developed to overcome the drawbacks of some traditional methods in highly nonlinear engineering optimization problems with high complexity, high dimension, and multimodal design spaces and to gain increasing popularity nowadays [1]. Performance assessment of a metaheuristic algorithm may be used by solution quality, computational effort, and robustness [2] directly affected by its two contradictory criteria: exploration of the search space (diversification) and exploitation of the best solutions found (intensification).

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

In this chapter a multi-objective optimization (MOP) is presented that uses the main concepts of charged system search algorithm (Kaveh and Massoudi [1]).

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

Discrete or continuous size optimization of large-scale, high-rise, or complex structures leads to problems with large number of design variables and large search space and requires the control of a great number of design constraints. Separate design decisions for each variable would be allowed. Thus, the optimizer invoked to process such a sizing problem is given the possibility to really optimize the objective function by detecting the optimum solution within a vast amount of possible design options. The huge number of available design options typically confuses an optimizer and radically decreases the potential of effective search for a high-quality solution. This chapter is based on the recent development on design of large-scale frame structures (Kaveh and Bolandgerami [1]).

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

In this chapter a newly developed metaheuristic method, so-called ray optimization, is presented. Similar to other multi-agent methods, ray optimization has a number of particles consisting of the variables of the problem. These agents are considered as rays of light. Based on the Snell’s light refraction law, when light travels from a lighter medium to a darker medium, it refracts and its direction changes. This behavior helps the agents to explore the search space in early stages of the optimization process and to make them converge in the final stages. This law is the main tool of the ray optimization algorithm. This chapter consists of three parts.

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

Particle swarm optimization (PSO) algorithms are nature-inspired population-based metaheuristic algorithms originally accredited to Eberhart, Kennedy, and Shi [1, 2]. The algorithms mimic the social behavior of birds flocking and fishes schooling. Starting form a randomly distributed set of particles (potential solutions), the algorithms try to improve the solutions according to a quality measure (fitness function). The improvisation is preformed through moving the particles around the search space by means of a set of simple mathematical expressions which model some interparticle communications. These mathematical expressions, in their simplest and most basic form, suggest the movement of each particle toward its own best experienced position and the swarm’s best position so far, along with some random perturbations. There is an abundance of different variants using different updating rules, however.

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

Although different metaheuristic algorithms have some differences in approaches to determine the optimum solution, however, their general performance is approximately the same. They start the optimization with random solutions, and the subsequent solutions are based on randomization and some other rules. With progressing the optimization process, the power of rules increases, and the power of randomization decreases. It seems that these rules can be modeled by a familiar concept of physics as well known as the fields of forces (FOF). FOF is a concept which is utilized in physics to explain the reason of the operation of the universe. The virtual FOF model is approximately simulated by using the concepts of real-world fields such as gravitational, magnetic, or electric fields (Kaveh and Talatahari [1]).

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

In the recent years, many metaheuristics with different philosophy and characteristics are introduced and applied to a wide range of fields. The aim of these optimization methods is to efficiently explore the search space in order to find global or near-global solutions. Since they are not problem specific and do not require the derivatives of the objective function, they have received increasing attention from both academia and industry.

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

This chapter consists of two parts. In the first part, an optimization algorithm based on some principles from physics and mechanics, which is known as the charged system search (CSS) [1]. In this algorithm the governing Coulomb law from electrostatics and the Newtonian laws of mechanics. CSS is a multi-agent approach in which each agent is a charged particle (CP). CPs can affect each other based on their fitness values and their separation distances. The quantity of the resultant force is determined by using the electrostatics laws, and the quality of the movement is determined using Newtonian mechanics laws. CSS can be utilized in all optimization fields; especially it is suitable for non-smooth or non-convex domains. CSS needs neither the gradient information nor the continuity of the search space.

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

In this chapter, tug of war optimization (TWO) is presented as a newly developed nature-inspired, population-based metaheuristic algorithm. Utilizing a sport metaphor, the algorithm considers each candidate solution as a team participating in a series of rope-pulling competitions. The teams exert pulling forces on each other based on the quality of the solutions they represent. The competing teams move to their new positions according to Newtonian laws of mechanics. Unlike many other metaheuristic methods, the algorithm is formulated in such a way that considers the qualities of both of the interacting teams. TWO is applicable to global optimization of discontinuous, multimodal, non-smooth, and non-convex functions.

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

In nature complex biological phenomena such as the collective behavior of birds, foraging activity of bees, or cooperative behavior of ants may result from relatively simple rules which however present nonlinear behavior being sensitive to initial conditions. Such systems are generally known as “deterministic nonlinear systems” and the corresponding theory as “chaos theory.” Thus real-world systems that may seem to be stochastic or random may present a nonlinear deterministic and chaotic behavior. Although chaos and random signals share the property of long-term unpredictable irregular behavior and many of random generators in programming softwares as well as the chaotic maps are deterministic; however chaos can help order to arise from disorder. Similarly, many metaheuristic optimization algorithms are inspired from biological systems where order arises from disorder. In these cases disorder often indicates both non-organized patterns and irregular behavior, whereas order is the result of self-organization and evolution and often arises from a disorder condition or from the presence of dissymmetries. Self-organization and evolution are two key factors of many metaheuristic optimization techniques. Due to these common properties between chaos and optimization algorithms, simultaneous use of these concepts can improve the performance of the optimization algorithms [1]. Seemingly the benefits of such combination are generic for other stochastic optimization, and experimental studies confirmed this although this has not mathematically been proven yet [2].

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

This chapter consists of two parts. In the first part, the standard magnetic charged system search (MCSS) is presented and applied to different numerical examples to examine the efficiency of this algorithm. The results are compared to those of the original charged system search method [1].

- Nov 2017
- Advances in Metaheuristic Algorithms for Optimal Design of Structures

This chapter presents a novel efficient metaheuristic optimization algorithm called colliding bodies optimization (CBO) for optimization. This algorithm is based on one-dimensional collisions between bodies, with each agent solution being considered as the massed object or body. After a collision of two moving bodies having specified masses and velocities, these bodies are separated with new velocities. This collision causes the agents to move toward better positions in the search space. CBO utilizes a simple formulation to find minimum or maximum of functions; also it is independent of parameters [1].

- Nov 2017

In today’s extremely competitive world, human beings attempt to exploit the maximum output or profit from a limited amount of available resources. In engineering design, for example, choosing design variables that fulfill all design requirements and have the lowest possible cost is concerned, i.e., the main objective is to comply with basic standards but also to achieve good economic results. Optimization offers a technique for solving this type of issues.

- Nov 2017

In this research, a newly developed nature-inspired optimization method, the Lion Pride Optimization algorithm (LPOA), is utilized for optimal design of composite steel box girder bridges. A composite box girder bridge is one of the common types of bridges used for medium spans due to their economic, aesthetic, and structural benefits. The aim of the present optimization procedure is to provide a feasible set of design variables in order to minimize the weight of the steel trapezoidal box girders. The solution space is delimited by different types of design constraints specified by the American Association of State Highway and Transportation Officials. Additionally, the optimal solution obtained by LPOA is compared to the results of other well-established meta-heuristic algorithms, namely Gray Wolf Optimization (GWO), Ant Lion Optimizer (ALO) and the results of former researches. By this comparison the capability of the LPOA in optimal design of composite steel box girder bridges is demonstrated.

- Oct 2017

Large-scale suspendomes are elegant architectural structures which cover a vast area with no interrupting columns in the middle. These domes have attractive shapes which are also economical. Domes are built in a wide variety of forms. In this article, an algorithm is developed for optimum design of domes considering the topology, geometry, and size of member section using the cascade-enhanced colliding bodies optimization method. In large-scale space steel structures, a large number of design variables are involved. The idea of cascade optimization allows a single optimization problem to be tackled in a number of successive autonomous optimization stages. The variables are the optimum height of crown and tubular sections of these domes, the initial strain, the length of the struts, and the cross-sectional areas of the cables in the tensegrity system of domes. The number of joints in each ring and the number of rings are considered for topology optimization of ribbed and Schwedler domes. Weight of the dome is taken as the objective function for minimization. A simple procedure is defined to determine the configuration of the domes. The design constraints are considered according to the provisions of Load and Resistance Factor Design–American Institute of Steel Constitution. In order to investigate the efficiency of the presented method, a large-scale suspendome with more than 2266 members is investigated. Numerical results show that the utilized method is an efficient tool for optimal design of large-scale domes. Additionally, in this article, a topology and geometry optimization for two common ribbed and Schwedler domes are performed to find their optimum graphs considering various spans.

- Sep 2017

Special kinds of structures exhibit repetitive patterns that can be used in the process of structural analysis in order to decrease the required computational time. This is especially helpful when a structure should be analyzed numerous times as in the structural optimization problems. In this article, weight optimization of cyclically symmetric spatial trusses subjected to frequency constraints is performed utilizing such repetitive patterns. Large initial eigenproblems are first decomposed into smaller and less time-consuming problems using an efficient block diagonalization technique. A recently developed meta-heuristic method, cyclical parthenogenesis algorithm, is then utilized to perform the optimization task. Three numerical examples are optimized to illustrate the viability and efficiency of the proposed method.

- Aug 2017

In this paper the performance of four well-known metaheuristics consisting of Artificial Bee
Colony (ABC), Biogeographic Based Optimization (BBO), Harmony Search (HS) and
Teaching Learning Based Optimization (TLBO) are investigated on optimal domain
decomposition for parallel computing. A clique graph is used for transforming the
connectivity of a finite element model (FEM) into that of the corresponding graph, and kmedian approach is employed. The performance of these methods is investigated through
four FE models with different topology and number of meshes. A comparison of the
numerical results using different algorithms indicates, in most cases the BBO is capable of
performing better or identical using less time with equal computational effort.

- Aug 2017

Labor productivity is one of the most important factors in achieving project success at different stages of a project. In this research, a new method is presented to model labor productivity for different types of contractors based on System Dynamic (SD) simulation. Using cause and effect feedback loops, a qualitative model is constructed. The relationships between different parameters are then determined by expert's judgment and real data obtained from several real projects, and the quantitative model is built. The labor productivity is simulated by the proposed SD model, considering all affecting factors. For higher accuracy, the model is examined on two types of contractors and two models are constructed. The total productivity of each contractor is obtained, and the effect of different parameters on the labor productivity is investigated.

- Aug 2017

The whale optimization algorithm (WOA) is a recently developed swarm-based optimization algorithm inspired by the hunting behavior of humpback whales. This study attempts to enhance the original formulation of the WOA by hybridizing it with some concepts of the colliding bodies optimization (CBO) in order to improve solution accuracy, reliability and convergence speed. The new method, called WOA-CBO algorithm, is applied to construction site layout planning problem. To show the efficiency and performance of the WOA and WOA-CBO in construction site layout problems, three case studies are selected. First case is a discrete and equal area facility layout problem that every facility could assign to any location. Second case is an unequal area version of discrete facility layout problem with more constraints and the last case is a continuous model of construction site layouts. These cases are studied by WOA, CBO and WOA-CBO, and the results are compared with each other.

- Aug 2017

Construction site layout planning is one of the managerial aspects of the construction industry and has significant impacts on performance of the sites. Since in real site layout optimization, many objectives are involved, therefore multi-objective algorithms are needed. In this study, multi-objective version of two meta-heuristics, CBO and ECBO, are developed and their applicability and performance are checked on a case study. The quality of the results obtained, verify the ability of these algorithms in finding optimal pareto front on this problem. Another tool that is utilized in this study is data envelopment analysis (DEA) which by calculating the efficiency of optimal pareto front layouts, can help decision makers to select the final layout among the candidates. It should be mentioned that the DEA has previously been used in models with multiple inputs and outputs.

- Aug 2017

Castellated beams and composite action of beams are widely applicable methods to increase the capacity of the beams. Semi-rigid connections can also redistribute internal moments in order to attain a better distribution. Combination of these methods helps to optimize the cost of the beam. In this study, some meta-heuristic algorithms consisting of the particle swarm optimization, colliding bodies optimization, and enhanced colliding bodies optimization are used for optimization of semi-rigid jointed composite castellated beams. Profile section, cutting depth, cutting angle, holes spacing, number of filled end holes of the castellated beams, and rigidity of connection are considered as the optimization variables. Constraints include the construction, moment, shear, deflection, and vibration limitations. Effects of partial fixity and commercial cutting shape of a castellated beam for a practical range of beam spans and loading types are studied through three numerical examples. The efficiency of three meta-heuristic algorithms is compared.

- Jul 2017

In cognitive science, it is illustrated how the collective opinions of a group of individuals answers to questions involving quantity estimation. One example of this approach is introduced in this article as Star Graph (SG) algorithm. This graph describes the details of communication among individuals to share their information and make a new decision. A new labyrinthine network of neighbors is defined in the decision-making process of the algorithm. In order to prevent getting trapped in local optima, the neighboring networks are regenerated in each iteration of the algorithm. In this algorithm, the normal distribution is utilized for a group of agents with the best results (guidance group) to replace the existing infeasible solutions. Here, some new functions are introduced to provide a high convergence for the method. These functions not only increase the local and global search capabilities but also require less computational effort. Various benchmark functions and engineering problems are examined and the results are compared with those of some other algorithms to show the capability and performance of the presented method.

- Jul 2017

The main purpose of this paper is to predict the properties (mechanical and rheological) of the self-compacting concrete (SCC) containing fly ash as cement replacement by using two decision tree algorithms: M5′ and Multivariate adaptive regression splines (Mars). The M5′ algorithm as a rule based method is used to develop new practical equations while the MARS algorithm besides its high predictive ability is used to determine the most important parameters. To achieve this purpose, a data set containing 114 data points related to effective parameters affect on SSC properties is used. A gamma test is employed to determine the most effective parameters in prediction of the compressive strength at 28 days, the V-funnel time, the slump flow, and the L-box ratio of SCC. The results from this study suggests that tree based models perform remarkably well in predicting the properties of the self-compacting concrete containing fly ash as cement replacement.

- Jul 2017

An efficient approach is presented for addressing the problem of finding the optimal facilities location in conjunction with the k-median method. First the region to be investigated is meshed and an incidence graph is constructed to obtain connectivity properties of meshes. Then shortest route trees (SRTs) are rooted from nodes of the generated graph. Subsequently, in order to divide the nodes of graph or the studied region into optimal k subregions, k-median approach is utilized. The weights of the nodes are considered as the risk factors such as population, seismic and topographic conditions for locating facilities in the high-risk zones to better facilitation. For finding the optimal facility locations, a recently developed meta-heuristic algorithm that is called Colliding Bodies Optimization (CBO) is used. The performance of the proposed method is investigated through different alternatives for minimizing the cost of the weighted k-median problem. As a case study, the Mazandaran province in Iran is considered and the above graph-metaheuristic approach is utilized for locating the facilities.

- Jul 2017

In this study, two different methods of data mining are used to develop new formulations for predicting the maximum bond strength force of near-surface-mounted fiber-reinforced polymer (FRP) systems in concrete. The advantages of each method are employed to find the most important parameters in estimating the maximum bond strength. A comprehensive database is used to develop new formulations for the maximum bond strength. Several effective parameters like geometrical and mechanical properties of the FRP, geometrical properties of the groove, bonded length, and concrete strength are involved in prediction of the maximum bond strength. The multivariate adaptive regression splines algorithm is implemented to accomplish sensitivity analysis. The results indicate that the geometry and mechanical properties of the FRP are the most important parameters. Alternatively, the M5′ algorithm as a rule-based method is employed to develop a more practical and simple model for estimating the maximum bond strength. Comparison of the developed models and the most common design codes demonstrates the superiority of the models in terms of the accuracy. Furthermore, the safety analysis based on demerit points classification scale also confirms the reliability of the proposed formulations.

- Jul 2017

Two-Dimensional Colliding Bodies Optimization (2D-CBO) is a new meta-heuristic algorithm based on two-dimensional collision laws. In this algorithm, like standard CBO, each agent is modeled as a body with a specified mass and velocity and collision occurs between pairs of objects, but unlike the standard CBO, the collision is based on two-dimensional law. In addition, a memory is added to the standard CBO for saving the best-so-far solution. In this paper, a new improved version of the 2D-CBO algorithm, namely Enhanced Two-Dimensional Colliding Bodies Optimization (E2D-CBO), is developed. E2D-CBO has a memory not only for saving the best-so-far solution, but also saving the number of best-so-far solutions and replacing them with the worst solutions in each iteration; moreover, it uses a mechanism to escape from local optima. By applying these changes, the exploitation ability and convergence rate of the 2D-CBO have been improved. The performance of this algorithm is compared to three recently developed meta-heuristic algorithms consisting of the standard CBO, Enhanced CBO and Two-Dimensional CBO algorithms on optimization of grillage system design. The results confirm the superiority of the E2D-CBO in comparison with the previous variants of the CBO algorithm.

- Jun 2017

Three different types of lateral resisting steel moment frames consisting of ordinary moment frame (OMF), intermediate moment frame (IMF) and special moment frame (SMF) are available for design of 3D frames in literature. In this paper, optimum seismic design of 3D steel moment frames with different types of lateral resisting systems are performed according to the AISC-LRFD design criteria. A comparison is made considering the results of the above mentioned frames of different ductility types. These frames are analyzed by Response Spectrum Analysis (RSA), and optimizations are performed using nine different well-established metaheuristic algorithms. Performances of these algorithms are then compared for introducing the most suitable metaheuristic algorithms for optimal design of the 3D frames.

- Jun 2017

In this study optimal design of reinforced concrete cantilever retaining walls is performed under static and earthquake loading conditions utilizing the Colliding Bodies of Optimization (CBO), Enhanced Colliding Bodies of Optimization (ECBO) and vibrating particles system (VPS) methods. This design is based on ACI 318-05 and two theories known as Coulomb and Rankine have been applied for estimating the earth pressures under static loading condition, and Mononobe-Okabe method have been applied for estimating earth pressures under earthquake loading condition. The objective function considered is the cost of the retaining wall and this function is minimized subjected to design constraints. The performances of the CBO, ECBO and VPS and some other optimization algorithms are compared for the considered benchmark examples.

- Jun 2017

Pitched roof frames are widely used in construction of the industrial buildings, gyms, schools and colleges, fire stations, storages, hangars and many other low rise structures. The weight and shape of the gable frames with tapered members, as a familiar group of the pitched roof frames, are highly dependent on the properties of the member cross-sectional. In this work Enhanced Colliding Bodies Optimization (ECBO) is utilized for optimal design of three gable frames with tapered members. In order to optimize the frames, the design is performed using the AISC specifications for stress, displacement and stability constraints. The design constraints and weight of the gable frames are computed from the cross-section of members. These optimum weights are obtained using aforementioned optimization algorithms considering the cross-sections of the members and design constraints as optimization variables and constraints, respectively. A comparative study of the PSO and CBO with ECBO is also performed to illustrate the importance of the enhancement of the utilized optimization algorithm.

- May 2017

The recently developed optimization algorithm—the so-called thermal exchange optimization (TEO) algorithm—is enhanced and applied to a damage detection problem. An offline parameter tuning approach is utilized to set the internal parameters of the TEO, resulting in the enhanced heat transfer optimization (ETEO) algorithm. The damage detection problem is defined as an inverse problem, and ETEO is applied to a wide range of structures. Several scenarios with noise and noise-free modal data are tested and the locations and extents of damages are identified with good accuracy.

- Apr 2017

In this article, a modified dolphin monitoring (MDM) operator is introduced and used to improve the performance of the colliding bodies optimization (CBO) algorithm for optimal design of steel structures (CBO MDM). The performance of the CBO, enhanced colliding bodies optimization (ECBO) and CBOMDM are compared through three well-established structural benchmarks. The optimized designs obtained by these algorithms are compared, and the results show that the performance of CBO-MDM is superior to those of the other two algorithms. The MDM is found to be a suitable tool to enhance the performance of the CBO algorithm.

- Apr 2017

In this article a hybrid algorithm based on a vibrating particles system (VPS) algorithm, multi-design variable configuration (Multi-DVC) cascade optimization, and an upper bound strategy (UBS) is presented for global optimization of large-scale dome truss structures. The new algorithm is called MDVC-UVPS in which the VPS algorithm acts as the main engine of the algorithm. The VPS algorithm is one of the most recent multi-agent meta-heuristic algorithms mimicking the mechanisms of damped free vibration of single degree of freedom systems. In order to handle a large number of variables, cascade sizing optimization utilizing a series of DVCs is used. Moreover, the UBS is utilized to reduce the computational time. Various dome truss examples are studied to demonstrate the effectiveness and robustness of the proposed method, as compared to some existing structural optimization techniques. The results indicate that the MDVC-UVPS technique is a powerful search and optimization method for optimizing structural engineering problems.

- Apr 2017

Purpose
There are many structures that have a repetitive pattern. If a relationship can be established between a repetitive structure and a circulant structure, then the repetitive structure can be analyzed by using the properties of the corresponding circulant structure. The purpose of this paper is to develop such a transformation.
Design/methodology/approach
A circulant matrix has certain properties that can be used to reduce the complexity of the analysis. In this paper, repetitive and near-repetitive structures are transformed to circulant structures by adding and/or eliminating some elements of the structure. Numerical examples are provided to show the efficiency of the present method.
Findings
A transformation is established between a repetitive structure and a circulant structure, and the analysis of the repetitive structure is performed by using the properties of the corresponding circulant structure.
Originality/value
Repetitive and near-repetitive structures are transformed to circulant structures, and the complexity of the analysis of the former structures is reduced by analyzing the latter structures.

- Apr 2017

In this paper, a newly developed multi-agent meta-heuristic method, named Cyclical Parthenogenesis Algorithm (CPA), is incorporated into a guided modal strain energy based structural damage detection technique. A modal strain energy based index is used to guide the structural damage identification process, which is formulated as an inverse optimization problem. Generalized Flexibility Matrix (GFM) of the structure is used to define the objective function of the optimization problem. Three numerical examples are provided in order to examine the viability of the proposed method. The results indicate that the proposed method is capable of locating and quantifying structural damage using only the first few modes of the structure. The results are also compared with those of three other meta-heuristic algorithms in order to show the efficiency of CPA in solving the problem.

- Apr 2017

This paper introduces a new optimization algorithm based on Newton's law of cooling, which will be called Thermal Exchange Optimization algorithm. Newton's law of cooling states that the rate of heat loss of a body is proportional to the difference in temperatures between the body and its surroundings. Here, each agent is considered as a cooling object and by associating another agent as environment, a heat transferring and thermal exchange happens between them. The new temperature of the object is considered as its next position in search space. The performance of the algorithm is examined by some mathematical functions and four mechanical benchmark problems.

- Apr 2017

In this paper a simple approach is presented for spectral matching of ground motions utilizing the wavelet transform and a recently developed metaheuristic optimization technique. For this purpose, wavelet transform is used to decompose the original ground motions to several levels, where each level covers a special range of frequency, and then each level is multiplied by a variable. Subsequently, the vibrating particles system (VPS) algorithm is employed to calculate the variables such that the error between the response and target spectra is minimized. The application of the proposed method is illustrated through modifying 12 sets of ground motions. The results achieved by this method demonstrate its capability in solving the problem. The outcomes of the VPS algorithm are compared to those of the standard colliding bodies optimization (CBO) to illustrate the importance of the enhancement of the algorithm.

- Apr 2017

In this paper, a new meta-heuristic algorithm based on free vibration of single degree of freedom systems with viscous damping is introduced, and it is called Vibrating Particles System (VPS). The solution candidates are considered as particles that gradually approach their equilibrium positions. Equilibrium positions are achieved from the current population and historically best position in order to have a proper balance between diversification and intensification. To evaluate the performance of the proposed method, it is applied to sizing optimization of four skeletal structures including trusses and frames. Results show that the proposed algorithm is a robust and reliable method.

- Feb 2017

Tower cranes are major and expensive equipment that are extensively used at building construction projects and harbors for lifting heavy objects to demand points. The tower crane locating problem to position a tower crane and supply points in a building construction site for supplying all requests in minimum time, has been raised from more than twenty years ago. This problem has already been solved by linear programming, but meta-heuristic methods spend less time to solving the problem. Hence, in this paper three newly developed meta-heuristic algorithms called CBO, ECBO, and VPS have been used to solve the tower crane locating problem. Three scenarios are studied to show the applicability and performance of these meta-heuristics.