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H.J.C. Barbosa^1,2, H.S. Bernardino² and J.S. Angelo¹

¹Laboratório Nacional de Computação Cientíica, Petrópolis, Rio de Janeiro, Brazil
²Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil

Keywords: multiobjective structural optimization, derivative-free, metaheuristic, surrogate model.

Abstract

In most real-world structural optimization problems one is concerned with more than a single objective. In fact, the objective functions are conflicting and possibly non-commensurable; hence there is no single solution that is optimal with respect to all objectives but rather a set of efficient solutions known as the Pareto-optimal set. The need for effective and efficient techniques to compute an approximation of the Pareto set in a single run thus is obvious. Due to the growing complexity of the problems tackled, derivative-free techniques in general, and nature-inspired metaheuristics in particular, are becoming increasingly popular. In this paper a critical review of the most relevant derivative-free techniques that have been applied to multiobjective structural optimization problems is offered together with current trends and suggestions for further work.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Computational Technology Reviews ISSN 2044-8430 Computational Technology Reviews Volume 12, 2015 Derivative-Free Techniques for Multiobjective Structural Optimization: A Review H.J.C. Barbosa^1,2, H.S. Bernardino² and J.S. Angelo¹ ¹Laboratório Nacional de Computação Cientíica, Petrópolis, Rio de Janeiro, Brazil ²Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil doi:10.4203/ctr.12.2 purchase the full-text of this paper Full Bibliographic Reference for this paper H.J.C. Barbosa, H.S. Bernardino, J.S. Angelo, "Derivative-Free Techniques for Multiobjective Structural Optimization: A Review", Computational Technology Reviews, vol. 12, pp. 27-52, 2015. doi:10.4203/ctr.12.2 Keywords: multiobjective structural optimization, derivative-free, metaheuristic, surrogate model. Abstract In most real-world structural optimization problems one is concerned with more than a single objective. In fact, the objective functions are conflicting and possibly non-commensurable; hence there is no single solution that is optimal with respect to all objectives but rather a set of efficient solutions known as the Pareto-optimal set. The need for effective and efficient techniques to compute an approximation of the Pareto set in a single run thus is obvious. Due to the growing complexity of the problems tackled, derivative-free techniques in general, and nature-inspired metaheuristics in particular, are becoming increasingly popular. In this paper a critical review of the most relevant derivative-free techniques that have been applied to multiobjective structural optimization problems is offered together with current trends and suggestions for further work. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to Computational Technology Reviews purchase this volume (price £75 +P&P)
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