David Greiner

Universidad de Las Palmas de Gran Canaria | ULPGC · Instituto Universitario de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

The paper presents an approach for simultaneous optimization of structural mass and reliability in discrete truss structures. In addition to member sizing, the selection of an optimal topology from a pre-specified ground structure is a feature of the proposed methodology. To allow for a global search, optimization is performed using a multiobjectiv...

A general review of game-theory based evolutionary algorithms (EAs) is presented in this study. Nash equilibrium, Stackelberg game and Pareto optimality are considered, as game-theoretical basis of the evolutionary algorithm design, and also, as problems solved by evolutionary computation. Applications of game-theory based EAs in computational engi...

This book results from the XVIII Spanish-French School 'Jacques Louis Lions' on Numerical Simulation in Physics and Engineering, that took place in Las Palmas de Gran Canaria from 25th to 29th June 2018. These conferences are held biennially since 1984 and sponsored by the Spanish Society of Applied Mathematics (SEMA). They also have the sponsorshi...

The approach of this paper is based on the evolutionary multi-objective optimization (EMO) of very thin noise barrier models with improved performance idealized as single-wire designs. To assume such a simplification of reality, the dual boundary element (DBE) formulation for assessing the acoustic efficiency arises as the most appropriate strategy...

Substation automation systems (SAS) are critical infrastructures whose design and maintenance must be optimised to guarantee a suitable performance. In order to provide a collection of solutions that balance availability and cost, this paper explores the optimisation of the design and maintenance of a section of SAS. Multiobjective evolutionary alg...

When projecting and building new industrial facilities, getting integrated design alternatives and maintenance strategies are of critical importance to achieve the physical assets optimal performance, which is needed to be competitive in the actual global markets. Coupling Evolutionary Algorithms with Discrete Event Simulation has been explored bot...

Industries that expect to optimize the performance of physical assets have to contemplate consider design alternatives and maintenance strategies from the phases of project and construction. The problem to be solved presents two objectives in conflict: maximising times in which the system is available and minimising costs due to both maintenance ac...

There is a growing interest in biomedical engineering in developing procedures that provide accurate simulations of the neural response to electrical stimulus produced by implants. Moreover, recent research focuses on models that take into account individual patient characteristics. We present a phenomenological computational model that is customiz...

Maximising profit is an important target for industries in a competitive world and it is possible to achieve this by improving the system availability. Engineers have employed many techniques to improve systems availability, such as adding redundant devices or scheduling maintenance strategies. However, the idea of using such techniques simultaneou...

Optimizing the system design and its maintenance strategy has to be considered when the best performance is expected. This chapter couples Multi-Objective Evolutionary Algorithms (MOEAs) and discrete-event simulation (DES) to explore systems’ design alternatives. It then explores the idea of preventive maintenance strategy with the aim of finding t...

Due to technical progress and business competition, design alternatives and maintenance strategies have to be contemplated to optimize the performance of physical assets when new facilities are projected and built. That combined optimization (Design & Maintenance) is required by all industrial installations to develop their activity in an increasin...

This book presents improved and extended versions of selected papers from EUROGEN 2019, a conference with interest on developing or applying evolutionary and deterministic methods in optimization of design and emphasizing on industrial and societal applications.

A novel phenomenological epidemic model is proposed to characterize the state of infectious diseases and predict their behaviors. This model is given by a new stochastic partial differential equation that is derived from foundations of statistical physics. The analytical solution of this equation describes the spatio-temporal evolution of a Gaussia...

Underwater gliders are energy-efficient vehicles that rely on changes in buoyancy in order to convert up and down movement into forward displacement. These vehicles are conceived as multi-sensor platforms, and can be used to collect ocean data for long periods in wide range areas. This endurance is achieved at the cost of low speed, which requires...

Purpose Impedance data obtained by electrochemical impedance spectroscopy ( EIS ) are fitted to a relevant electrical equivalent circuit to evaluate parameters directly related to the resistance and the durability of metal–coating systems. The purpose of this study is to present a novel and more efficient computational strategy for the modelling of...

Game-theory based Nash–evolutionary algorithms are efficient to speed-up and parallelize the optimum design procedure. They have been applied in several fields of engineering and sciences, mainly, in aeronautical and structural engineering. The influence of the search space player territory has been shown as having an important role in the algorith...

This paper presents a new procedure to design optimal electrodes for cochlear implants. The main objective of this study is to find a set of electrode designs that maximize the focalization and minimize the power consumption simultaneously. To achieve that, a criterion to measure the ability of focalization of an electrode is proposed. It is presen...

The use of evolutionary algorithms has been enhanced in recent years for solving real engineering problems, where the requirements of intense computational calculations are needed, especially when computational engineering simulations are involved (use of finite element method, boundary element method, etc). The coupling of game-theory concepts in...

This paper presents a Boundary Elements (BE) approach for the efficiency improvement of road acoustic barriers, more specifically, for the shape design optimization of top-edge devices in the search for the best designs in terms of screening performance, usually represented by the insertion loss (IL). With this aim, a procedure coupling BE with Evo...

A parallel implementation of a game-theory based Nash Genetic Algorithm (Nash-GAs) is presented in this paper for solving reconstruction inverse problems in structural engineering. We compare it with the standard panmictic genetic algorithm in a HPC environment with up to eight processors. The procedure performance is evaluated on a fifty-five bar...

Electrochemical Impedance Spectroscopy (EIS) is a powerful tool in the characterization of organic coated metal systems because the method can give both qualitative and quantitative information regarding their behavior. Impedance data are fitted to a relevant electrical equivalent circuit in order to evaluate parameters directly related to the resi...

In this paper we deal with solving inverse problems in structural engineering (both the reconstruction inverse problem and the fully stressed design problem are considered). We apply a game-theory based Nash-evolutionary algorithm and compare it with the standard panmictic evolutionary algorithm. The procedure performance is analyzed on a ten bar s...

This paper reviews the combination of Artificial Neural Networks (ANN) and Evolutionary Optimisation (EO) to solve challenging problems for the academia and the industry. Both methodologies has been mixed in several ways in the last decade with more or less degree of success, but most of the contributions can be classified into the two following gr...

This paper presents a Boundary Elements (BE) approach for the efficiency improvement of road acoustic barriers, more specifically, for the shape design optimization of top-edge devices in the search for the best designs in terms of screening performance, usually represented by the inser- tion loss (IL). With this aim, a procedure coupling BE with E...

A procedure for improving the acoustic efficiency of barriers featuring top-edge devices is conducted. This methodology is based on the maximization of the insertion loss of candidate profiles proposed by an evolutionary algorithm. The complexity normally associated with these devices raises the need to consider some geometric simplifications in or...

Evolutionary Algorithms and Metaheuristics are used extensively and with growing interest in wide areas of applied sciences and engineering for solving real application problems of interest in industry and society. This book focuses on civil and structural engineering and construction management applications. Particularly, in recent years, differen...

The optimization structural design problems of Fully Stressed Design (FSD) and Minimum Constrained Weight (MCW) are compared in this work in a simple truss test case with discrete cross-section type bar sizing, where both optimum designs are coincident. An analysis of the whole search space is included, and the optimization behaviour of evolutionar...

Los autores de este artículo trabajan desde hace algunos años en la formulación e implementación de procedimientos numéricos que permiten proponer geometrías de pantalla anti-ruido que sean acústicamente más eficientes. Así, desde unos requisitos previos que definen la tipología del problema, estos procedimientos utilizan modelos de búsqueda de ópt...

The inclusion of sound barriers for abating road traffic noise is a broadly used strategy that is often constrained by the requirements associated with its effective height. Due to this fact, the searching process has to deal with compromise solutions between the effective height and the acoustic efficiency of the barrier, assessed by the insertion...

This work aims at assessing the acoustic efficiency of different thin noise barrier models. These designs frequently feature complex profiles and their implementation in shape optimization processes may not always be easy in terms of determining their topological feasibility. A methodology to conduct both overall shape and top edge optimizations of...

The paper examines the influence of including buckling constraints in the multiobjective optimization of truss structures for minimal mass and maximal reliability. Uncertainties in external loads and material properties are included in the structural analysis and evolutionary multiobjective optimization algorithms are used to establish the non-domi...

This work aims at assessing the acoustic efficiency of different thin noise barrier models. These designs frequently feature complex profiles and their implementation in shape optimization processes may not always be easy in terms of determining their topological feasibility. A methodology to conduct the shape design optimization of thin cross sect...

In this lecture we solve the fully stressed design problem in structural engineering using a game-theory based Nash – Genetic algorithm (Nash-GAs). The procedure performance is analyzed on different set of variable splitting of the problem in a fifty-five bar sized test case of discrete real cross-section types bar structure and compared also with...

Lorsque l’on traite des problèmes d’optimisation réels de complexité NP-difficile et des objectifs à satisfaire contradictoires, les Algorithmes Évolutionnaires Multi-Objectif (AEMO) ont prouvé obtenir d’excellents résultats. Une classification récente des AEMO proposée par Branke, comprend une approche -AEMO sous préférences partielles- intermédia...

This paper proposes the incorporation of engineering knowledge through both (a) advanced state-of-the-art preference handling decision-making tools integrated in multiobjective evolutionary algorithms and (b) engineering knowledge-based variance-reduction simulation as enhancing tools for the robust optimum design of structural frames taking uncert...

This paper is concerned with the influence of the codification type on the optimization of frame structures for constrained minimum weight, when using discrete variables: cross-section types corresponding to standard profiles. Three different codifications are compared: standard binary, standard reflected gray, and other binary codification with a...

An optimization methodology to evaluate simultaneously optimum designs of multiple slope height values with their corresponding factors of safety is proposed in this paper when considering the problem of slope stability. Limit equilibrium methods and evolutionary computation are used as analysis and optimization tools, respectively. The slip surfac...

Considering uncertainties in engineering optimum design is often a requirement. Here, the use of the deterministic optimum design as the reference point in g-dominance is proposed. The multiobjective optimum robust design in a structural engineering test case where uncertainties in the external loads are taken into account is proposed as applicatio...

Structural frames robust optimum design under uncertain loads is handled simultaneously minimizing the constrained mass (adding structural mass and constraint average distribution), as well as the constraint violation distribution standard deviation, using the non-dominated sorting genetic algorithm NSGA-II. The consideration of external loads as r...

The optimum shape design of Y-noise barriers is carried out using single and multi-objective evolutionary algorithms and the Boundary Element Method (BEM). Reduction of noise impact efficiency (using the insertion loss-IL-magnitude) and cost of the barrier (using its total length magnitude) are considered. A two-dimensional problem of sound propaga...

This paper shows a method to compute the chord and twist distributions in wind power blades. The distributions are computed to maximize the mean expected power depending on the Weibull wind distribution at a specific site. This approach avoids assumptions about optimal attack angle related to the ratio between the lift to drag coefficients. To opti...

Multiobjective shape design of acoustic attenuation barriers is handled using a boundary element method modeling and evolutionary algorithms. Noise barriers are widely used for environmental protection near population nucleus in order to reduce the noise impact. The minimization of the acoustic pressure and the minimization of the cost of the barri...

The so called second generation of Multi-Objective Evolutionary Algorithms (MOEAs) like NSGA-II, are highly efficient and obtain Pareto optimal fronts characterized mainly by a wider spread and visually distributed fronts. The subjacent idea is to provide the decision-makers (DM) with the most representative set of alternatives in terms of objectiv...

En el presente trabajo se describen las metodologías necesarias para realizar la optimización desde criterios, tanto económicos como de confiabilidad, de sistemas industriales complejos. Se utiliza como ejemplo ilustrativo la optimización conjunta del diseño y la estrategia de man-tenimiento de un sistema de seguridad de una central nuclear. Las me...

Without Abstract

Considering evolutionary multiobjective algorithms for improving single objective optimization problems is focused in this work on introducing the concept of helper objectives in a computational mechanics problem: the constrained mass minimization in real discrete frame bar structures optimum design. The number of different cross-section types of t...

Shape optimum design of M-shaped noise barriers is carried out using BEM for modelling and evolutionary algorithms for optimization. The sound level is calculated being known: The source position, the receptor position, the barrier shape, and the sound frequency. The fitness function to minimize is the sum of squared differences corresponding to th...

Controlled elitism in NSGAII is analysed, applied to a multiobjective frame optimisation problem with discrete modelling. Influence of various mutation rates is considered. A double minimization is handled: constrained weight and number of different cross section types. The comparative statistical results of the test case show a convergence study d...

This paper introduces an algorithm for the maximization of the spreading factor of Pareto fronts. A set of synthetic functions is used to contrast the spreading of our approach against the one produced by NSGA-II and SPEA-2. A bi-objective structural optimization design problem with constraints is also solved with the proposed technique. The goal i...

The multiobjective or multicriteria optimum design of structural trusses is handled in this paper. A double minimization is taken into account: constrained mass and number of different cross-section types. The first fitness function, the constrained mass, considers constraints in terms of stresses, buckling effect and displacements of certain nodes...

Considering evolutionary multiobjective algorithms for improving single objective optimization problems is focused in this work on introducing the concept of helper objectives in a computational mechanics problem: the constrained mass minimization in real discrete frame bar structures optimum design. The number of different cross-section types of t...

Structural design optimization has been applied, in many structural types, including trusses and frames, mainly oriented to the mass minimization. An additional consideration is the sensitivity of these obtained optimum designs to load variations. Striving after a null constraint violation, even under this possible load variation, simultaneously wi...

Evolutionary algorithms have been widely used for Shape Design Optimization. It is a problem handled in many fields of science and engineering, e.g., aeronautics or solid mechanics. In this work we propose the application of this methodology based on evolutionary algorithms, to the shape design of a noise barrier. Noise Barriers are widely used for...

A comparative study of the use of Gray coding in multicriteria evolutionary optimisation is performed using the SPEA2 and NSGAII algorithms and applied to a frame structural optimisation problem. A double minimization is handled: constrained mass and number of different cross-section types. Influence of various mutation rates is considered. The com...

Since it has currently became essential to design more efficient and robust alternative techniques to solve hard optimisation problems in industry or science, and of easy use for practitioners, here a new way of developing simple Artificial Intelligence based Evolutionary Algorithms will be introduced. Our evolutionary computational implementation...

This chapter proposes a solution to a state constrained optimal control problem with parallel implementations of an intelligent optimization system based on evolutionary self-learning named flexible evolution agent (FEA). The agent has a dynamic structure of operators (DSO), enlargement of the genetic code (EGC) of each candidate solution, and uses...

The constrained minimum-mass problem of middle-size frames is taken into account, for both continuous and discrete cases with ideal (without buckling effect and own gravitational load) and real (with both) models, comparing three strategies of evolutionary algorithms. Some proposals to obtain appropriate results in middle-sized frames are exposed:...

This paper attempts to present a summarized survey in the field of Parallel Evolutionary Algorithms (PEAs), trying to highlight the most relevent aspects in the design and implementation of each class of PEAs. A review of the most advanced research activities on this field is presented. New tools for new challenges of industry and society, which ar...

Elitism has been proved to improve the behaviour of multiobjective evolutionary algorithms. Ways to favour the increment of diversity in the population are recently proposed. Duplicate elimination is showed as an operator that can increase the performance of elitist algorithms. A statistical study of the interaction of this operator with the elitis...

Multiobjective evolutionary methods have acquired relevance because of the lack of disadvantages that the classic multiobjective methods have. They allow locating the whole Pareto frontier in a single run—depending on the value of fitness. With this frontier, the designer selects the solution that better fits into one's requirements. This chapter b...

In this work new safety systems multiobjective optimum design methodologies are introduced and compared. Various multicriteria evolutionary algorithms are analysed (SPEA2, NSGAII and controlled elitist-NSGAII) and applied to a Containment Spray Injection System of a nuclear power plant. Influence of various mutation rates is considered. A double mi...

Two frame structure optimisation problems are handled. Firstly, the constrained minimum-mass problem, for which both continuous and discrete cases with ideal (without buckling effect and its own gravitational load) and real (with buckling effect and its own gravitational load) models are solved with several types of genetic algorithms. Results for...

The unit commitment (UC) and Economic Dispatch (ED) are important part of the set of actions included in the concept of Power Systems Operation. In this paper we describe the application of Genetic Algoritms (GAs) to UC and ED problems using both binary and real coding, with increased efficiency because the use of Convergence Accelerators derived f...

El objetivo del trabajo es incrementar la eficiencia computacional por reducción del tratamiento de la función objetivo introduciendo un patrón en el esquema que se acerque a la solución deseada. Con ello se reduce el cálculo de la función objetivo que en casi todos los casos representa aproximadamente el 80% de computación. El cromosoma patrón es...