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Performance evaluation of local surrogate models in differential evolution-based optimum design of truss structures

Eduardo Krempser (Programa Institucional Biodiversidade e Saúde, Fundação Oswaldo Cruz, Rio de Janeiro, Brasil)
Heder S. Bernardino (Departamento de Ciência da Computação, Universidade Federal de Juiz de Fora, Juiz de Fora, Brasil)
Helio J.C. Barbosa (Laboratório Nacional de Computação Científica, Petrópolis, Brasil and Departamento de Ciência da Computação, Universidade Federal de Juiz de Fora, Juiz de Fora, Brasil)
Afonso C.C. Lemonge (Departamento de Mecânica Aplicada e Computacional, Universidade Federal de Juiz de Fora, Juiz de Fora, Brasil)

Engineering Computations

ISSN: 0264-4401

Article publication date: 18 April 2017

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Abstract

Purpose

The purpose of this paper is to propose and analyze the use of local surrogate models to improve differential evolution’s (DE) overall performance in computationally expensive problems.

Design/methodology/approach

DE is a popular metaheuristic to solve optimization problems with several variants available in the literature. Here, the offspring are generated by means of different variants, and only the best one, according to the surrogate model, is evaluated by the simulator. The problem of weight minimization of truss structures is used to assess DE’s performance when different metamodels are used. The surrogate-assisted DE techniques proposed here are also compared to common DE variants. Six different structural optimization problems are studied involving continuous as well as discrete sizing design variables.

Findings

The use of a local, similarity-based, surrogate model improves the relative performance of DE for most test-problems, specially when using r-nearest neighbors with r = 0.001 and a DE parameter F = 0.7.

Research limitations/implications

The proposed methods have no limitations and can be applied to solve constrained optimization problems in general, and structural ones in particular.

Practical/implications

The proposed techniques can be used to solve real-world problems in engineering. Also, the performance of the proposals is examined using structural engineering problems.

Originality/value

The main contributions of this work are to introduce and to evaluate additional local surrogate models; to evaluate the effect of the value of DE’s parameter F (which scales the differences between components of candidate solutions) upon each surrogate model; and to perform a more complete set of experiments covering continuous as well as discrete design variables.

Keywords

Acknowledgements

The authors would like to thank Dr Oguzhan Hasançebi for kindly providing the data for the 942-bar truss structure. The authors acknowledge the support from CNPq (Grants 310778/2013-1 and 305099/2014-0) and FAPEMIG (Grants TEC PPM 528/11, TEC PPM 388/14 and APQ-03414-15).

Citation

Krempser, E., Bernardino, H.S., Barbosa, H.J.C. and Lemonge, A.C.C. (2017), "Performance evaluation of local surrogate models in differential evolution-based optimum design of truss structures", Engineering Computations, Vol. 34 No. 2, pp. 499-547. https://doi.org/10.1108/EC-06-2015-0176

Publisher

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Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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