Ali Sadollah

University of Science and Culture · Department of Mechanical Engineering

The continuous supply of drinking water for human life is essential to ensure the sustainability of cities, society, and the environment. At a time when water scarcity is worsening due to climate change, the construction of an optimized water supply infrastructure is necessary. In this study, an improved version of the Harmony Search Algorithm (HSA...

A distributed heterogeneous permutation flowshop scheduling problem with sequence‐dependent setup times (DHPFSP‐SDST) is addressed, which well reflects real‐world scenarios in heterogeneous factories. The objective is to minimise the maximum completion time (makespan) by assigning jobs to factories, and sequencing them within each factory. First, a...

Optimising the shape and size of large-scale truss frames is challenging because there is a nonlinear interaction between cross-sectional and nodal coordinate forces of structures. Meanwhile, combining the shape and bar size variables creates a multi-modal search space with dynamic constraints, making an expensive optimisation engineering problem....

Optimising the shape and size of large-scale truss frames is challenging because there is a nonlinear interaction between cross-sectional and nodal coordinate forces of structures. Meanwhile, combining the shape and bar size variables makes a multi-modal search space with dynamic constraints that makes an expensive optimisation problem. Besides, mo...

This contributed book focuses on optimization methods inspired by nature such as Harmony Search Algorithm, Drosophila Food-Search Algorithm, Cohort intelligence algorithm and its variations, fuzzy logic along with their hybridization variants. It also focuses on multi-objective optimization algorithms such as Non-Dominated Sorting Genetic Algorithm...

Swarm intelligence is a relatively recent approach for solving optimization problems that usually adopts the social behavior of birds and animals. The most popular class of swarm intelligence is ant colony optimization (ACO), which simulates the behavior of ants in seeking and moving food. This chapter aim to briefly overview the important role of...

At present, home health care (HHC) has been accepted as an effective method for handling the healthcare problems of the elderly. The HHC scheduling and routing problem (HHCSRP) attracts wide concentration from academia and industrial communities. This work proposes an HHCSRP considering several care centers, where a group of customers (i.e., patien...

Neural Network Algorithm (NNA) is a recently proposed Metaheuristic that is inspired by the idea of artificial neural networks. The performance of NNA on single-objective optimization problems is very promising and effective. In this article, a maiden attempt is made to restructure NNA for its possible use to address multi-objective optimization pr...

The generation rescheduling is described as the power generation shifting from one or more generators to one or more other generators as a preventive action to improve and maintain the security of the power system. Since, there is a direct link between security improvement and the lines overload under contingencies, by rescheduling generation, the...

There has been an advance toward the development of many metaheuristic optimization algorithms inspired by various natural and artificial phenomena. While any algorithm should be coded to each particular optimization problem, an increase in interest arises for the development of software that can generally and effectively function. HS-Solver is an...

Path planning of uninhabited combat air vehicle (UCAV) is a rather complicated global optimum problem which is about seeking a superior flight route considering different kinds of constrains under complex combat field environment. Neural network algorithm (NNA) is a recently developed optimizer inspired by the unique structure of artificial neural...

In this study, low-velocity impact on fiber metal laminate (FML) plate with nanoclay reinforcement particles has been investigated. Rectangular FML specimens have been made by hand lay-up method using two 2024 aluminum sheets and 4 layers of basalt fibers. The ultrasonic device is used for nanoclay in samples, and the specimens are constructed in d...

Gearing is one of the most efficient methods of transmitting power from a source to its application with or without change of speed or direction. In this paper, a spur gear model is optimized aiming to maximize its transmission power and minimize its weight. Several design variables named as transmitted power, number of pinion teeth, modules, and t...

In this paper, a net-zero energy building setup over an existing building in the suburbs of Melbourne city is proposed. Based on the power consumption, a solar panel system considering minimum size is done to determine the optimum number of solar panels required for the building. An anisotropic method is utilized to model the incident radiation. Fo...

Currently, population aging has aroused much concern in many countries since the elderly occupy a lot of social public resources in hospitals and nursing homes. Home health care (HHC) is treated as an alternative solution to serve the elderly community. In recent years, managing and organizing the operation of HHCs receive a great deal of attention...

In this paper, conductive polymer-based composites in order to have higher electrical conductivity have been constructed using different nanoparticles and numerically considered by different classification techniques. Due to non-conducting feature of polymer-based composites, their other positive advantages (e.g., light weight and stress corrosion)...

Minimum cost of energy is the main goal of a wind farm layout optimization. This is achieved by maximizing the total energy while minimizing the total costs of the farm. In this study, two sizes of commercial turbines were considered to investigate the effect of a non-homogenous farm on the layout optimization process. A cost model consisting of tu...

In order to develop the dynamic effectiveness of the structures such as trusses, the application of optimisation methods plays a significant role in improving the shape and size of elements. However, conjoining two heterogeneous variables, nodal coordinates and cross-sectional elements, makes a challenging optimisation problem that is nonlinear, mu...

There has been an advance toward the development of many metaheuristic optimization algorithms inspired by various natural and artificial phenomena. While any algorithm should be coded to each particular optimization problem, an increase in interest arises for the development of software that can generally and effectively function. HS-Solver is an...

Production and distribution are two important sectors in a supply chain and their managements become an essential issue in industrial fields. The integrated operation of production and distribution stages are regarded as an effective approach. This work proposes an integrated production and distribution optimization problem, where jobs are processe...

In recent years, many researchers have utilized metaheuristic optimization algorithms along with fuzzy logic theory in their studies for various purposes. The harmony search (HS) algorithm is one of the metaheuristic optimization algorithms that is widely employed in different studies along with fuzzy logic (FL) theory. FL theory is a mathematical...

Generally, scheduling problems refer to allocation of available shared resources and the sorting of production tasks, in order to satisfy the specified performance target within a certain time. The fundamental scheduling problem is that all jobs need to be processed on the same route, which is called flow shop scheduling problems (FSSP). The goal o...

Production and distribution are two essential activities in supply chain management. Currently, integrated production and distribution problems receive much attention because decision-makers devote to improving the operation efficiency of both stages and try to achieve an optimal solution. This work proposes an integrated distributed production and...

This paper represents a hybrid Firefly and Self-Regulating Particle Swarm Optimization (FSRPSO) algorithm to solve optimal Combined Heat and Power Economic Dispatch (CHPED) problem. Valve point effect on fuel cost function of pure generation units, electrical power losses in transmission systems and feasible operating zones are taken into account i...

Extreme learning machine (ELM) is a non-iterative algorithm for training single-hidden layer feedforward neural network (SLFN). ELM has been shown to have good generalization performance and faster learning speed than conventional gradient-based learning algorithms. However, due to the random determination of the hidden neuron parameters (i.e., inp...

In recent years, significant attentions have been devoted to design of metaheuristic optimization algorithms in order to solve optimization problems. Metaheuristic optimizers are methods which are inspired by observing the phenomena occurring in nature. In this paper, a comprehensive and exhaustive review has been carried out on water cycle algorit...

Distributed generation (DG) resources based on solar and wind energies are among the DGs that can optimize the voltage profile and reduce network losses by optimal locating and sizing in distribution systems. In this paper, 4-Rule Harmony Search (4-RHS) algorithm is presented for optimal placement and sizing of the renewable DG resources. In this r...

This study proposes a novel detection model for the detection of cyber-attacks using remote sensing data on water distribution systems (i.e., pipe flow sensor, nodal pressure sensor, tank water level sensor, and programmable logic controllers) by machine learning approaches. The most commonly used and well-known machine learning algorithms (i.e., k...

In this paper, Neural Network Algorithm is employed for simultaneous placing and sizing Distributed Generators and Shunt Capacitors Banks in distribution network to minimize active power loss and improve the voltage profile. The NNA is a novel developed optimizer based on the concept of artificial neural networks which benefits from its unique stru...

Internationally, there are heightened demands for efficient public transportation systems due to high population growth rates in urban areas and their associated increased trip demands within and across city boundaries. An ideal and sustainable public transportation system should satisfy its passengers while minimizing operation costs that are ofte...

In this article, a model of a T-shaped fin, consisting of a set of ordinary differential equations (ODEs), is considered. The purpose of this article is to numerically solve ODE systems of a T-shaped fin (there is no reported exact and analytical solution) using an alternative approach. Utilizing a base approximation function, some mathematical pri...

Harmony Search (HS) is a music-inspired optimization algorithm for solving complex optimization problems that imitate the musical improvisational process. This paper reviews the potential of applying the HS algorithm in three countries, China, South Korea, and Japan. The applications represent several disciplines in fields of study such as computer...

Various metaheuristic optimization algorithms are being developed to obtain optimal solutions to real-world problems. Metaheuristic algorithms are inspired by various metaphors, resulting in different search mechanisms, operators, and parameters, and thus algorithm-specific strengths and weaknesses. Newly developed algorithms are generally tested u...

In this article, a self-adaptive global mine blast algorithm (GMBA) is proposed for numerical optimization. This algorithm is designed in a novel way, and a new shrapnel equation is proposed for the exploitation phase of mine blast algorithm. A theoretical study is performed, which proves the convergence of any typical shrapnel piece; a new definit...

In recent years, both sustainability and optimization concepts have become inseparable developing topics with diverse concepts, elements, and aspects. The principal goal of optimization is to improve the overall sustainability including the environmental sustainability, social sustainability, economic sustainability, and energy resources sustainabi...

This paper proposes an enhanced harmony search algorithm for solving computationally expensive benchmarks widely used in the literature. We explored the potential and applicability of the original harmony search (HS) algorithm through introducing an extended version of the algorithm integrated with a new dynamic search equation enabling the algorit...

Optimal power flow (OPF) is a key tool for planning and operations in energy grids. The line-flow constraints, generator loading effect, piece-wise cost functions, emission, and voltage quality cost make the optimization model non-convex and computationally cumbersome to solve. Metaheuristic techniques for solving the problem have emerged as a prom...

Recently, many manufacturing enterprises pay closer attention to energy efficiency due to increasing energy cost and environmental awareness. Energy-efficient scheduling of production systems is an effective way to improve energy efficiency and to reduce energy cost. During the past 10 years, a large amount of literature has been published about en...

Engineering benchmark problems with specific characteristics have been used to compare the performance and reliability of metaheuristic algorithms, and water distribution system design benchmarks are also widely used. However, only a few benchmark design problems have been considered in the research community. Due to the limited set of previous ben...

The minimum cost of energy is the goal of wind farm layout optimization. This can be achieved by maximizing the total energy and minimizing the total costs of the farm. This study considered two sizes of commercial turbines and thus we modified the simple cost model proposed by Mosetti et al. [1], using cost scaling law. We also used Jensen wake mo...

Water cycle algorithm (WCA) is a population-based metaheuristic algorithm, inspired by the water cycle process and movement of rivers and streams towards sea. The WCA shows good performance in both exploration and exploitation phases. Further, the relationship between improvised exploitation and each parameter under asymmetric interval is derived a...

This paper presents a synthesis strategy for impact force localization and identification of framed structures in time-domain using a two-step wavelet-based fitness evaluation scheme in conjunction with genetic and water cycle algorithms. For this purpose, a straightforward approach is developed for sensitivity analysis of accelerations and spatial...

Traffic congestion is a critical problem which makes roads busy. Traffic congestion challenges traffic flow in urban areas. A growing urban area creates complex traffic problems in daily life. Congestion phenomena cannot be resolved only by applying physical constructs such as building bridges and motorways and increasing road capacity. It is neces...

The Neural Network Algorithm has been written in MATLAB programming language. This code is for solving constrained continuous optimization problems using feasible approach (Direct method proposed by Deb 2001). Enjoy it!

The Water Cycle Algorithm has been written in MATLAB programming language. This code is for solving unconstrained continuous optimization problems. Enjoy it!

The Neural Network Algorithm has been written in MATLAB programming language. This code is for solving unconstrained continuous optimization problems. Enjoy it!

The Neural Network Algorithm has been written in MATLAB programming language. This code is for solving constrained continuous optimization problems using feasible approach (Direct method proposed by Deb 2001). Enjoy it!

The Neural Network Algorithm has been written in MATLAB programming language. This code is for solving unconstrained continuous benchmark problems. Enjoy it!

The Water Cycle Algorithm has been written in MATLAB programming language. This code is for solving constrained continuous optimization problems using feasible approach (Direct method proposed by Deb 2001). Enjoy it!

The water cycle algorithm (WCA) is a nature-inspired meta-heuristic recently contributed to the community in 2012, which finds its motivation in the natural surface runoff phase in water cycle process and on how streams and rivers flow into the sea. This method has been so far successfully applied to many engineering applications, spread over a wid...

In this research, a new metaheuristic optimization algorithm, inspired by biological nervous systems and artificial neural networks (ANNs) is proposed for solving complex optimization problems. The proposed method, named as neural network algorithm (NNA), is developed based on the unique structure of ANNs. The NNA benefits from complicated structur...

This paper proposes a hybrid optimization method that combines the power of the harmony search (HS) with the mine blast algorithm (MBA). The resulting mine blast harmony search (MBHS) uses MBA for exploration and HS for exploitation. The HS is inspired by the improvisation process of musicians, while the MBA is derived based on explosion of landmin...

روش های بهینه سازی فراابتکاری دریچه ای نو به سوی حل مسائل مهندسی، کامپیوتر و علوم پایه گشوده است. در محاسبات سنگین تحلیلی در عرصه خودروسازی و هوافضا، الگوریتم های بهینه سازی هوشمند، نقش بسزایی در بهینه کردن پارامترهای ساخت و طراحی ایفا می کنند. آشنایی با روش های بهینه سازی، ابزاری مهم و حیاتی در اختیار طراحان، مهندسان و سازندگان قرار می دهد تا با...

Public transportation can have an efficient role ingainingtraveler satisfaction while decreasing operation costs through establishing an integrated public transit system. The main objective of this research is to propose an integrated multimodal transit model to design the best combination of both railway and feeder bus mode transit systems, while...

Defining true and false as response to most real life's problems is a superficial view. Real life and new proposed problems are going to be more and more complex in terms of size and other aspects such as non-linearity. Increasing complexity of problems need more information. When using Fuzzy Logic there is no need of a detailed knowledge of a syst...

This paper describes the enhancement of the water cycle algorithm (WCA) using a fuzzy inference system to dynamically adapt its parameters. The original WCA is compared in terms of performance with the proposed method called WCA with dynamic parameter adaptation (WCA-DPA). Simulation results on a set of well-known test functions show that the WCA i...

In this article, scheduling and rescheduling problems with increasing processing time and new job insertion are studied for reprocessing problems in the remanufacturing process. To handle the unpredictability of reprocessing time, an experience-based strategy is used. Rescheduling strategies are applied for considering the effect of increasing repr...

Portfolio selection is one of the most vital financial problems in literature. The studied problem is a nonlinear multi-objective problem which has been solved by a variety of heuristic and metaheuristic techniques. In this article, a metaheuristic optimiser, the multi-objective water cycle algorithm (MOWCA), is represented to find efficient fronti...

This paper studies a large-scale urban traffic light scheduling problem (LUTLSP). A centralized model is developed to describe the LUTLSP, where each outgoing flow rate is described as a nonlinear mixed logical switching function over the source link’s density, the destination link’s density and capacity, and the driver’s potential psychological re...

This paper proposes a harmony search algorithm-based optimization of design and operation of hydropower storage systems. The optimization formulation of the problem is a nonconvex nonlinear program difficult to solve by gradient-based nonlinear programming techniques. The search space of the problem is large due to number of operational variables....

The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvan...