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Computational Technology Reviews
ISSN 2044-8430
Computational Technology Reviews
Volume 12, 2015
Derivative-Free Techniques for Multiobjective Structural Optimization: A Review
H.J.C. Barbosa1,2, 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

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.

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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