Ant colony approaches for multiobjective structural optimization problems with a cardinality constraint

被引：48

作者：

Angelo, Jaqueline S. ^{[1
]}

Bernardino, Heder S. ^{[2
]}

Barbosa, Helio J. C. ^{[1
,2
]}

机构：

[1] Lab Natl Computacao Cient, Petropolis, RJ, Brazil

[2] Univ Fed Juiz de Fora, Juiz De Fora, MG, Brazil

来源：

ADVANCES IN ENGINEERING SOFTWARE | 2015年 / 80卷

关键词：

Structural optimization; Cardinality constraint; Multiobjective optimization; Ant colony algorithm; Adaptive penalty; Multicriteria tournament decision; ADAPTIVE PENALTY SCHEME; GENETIC ALGORITHMS; OPTIMAL-DESIGN;

D O I：

10.1016/j.advengsoft.2014.09.015

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Two Ant Colony Optimization algorithms are proposed to tackle multiobjective structural optimization problems with an additional constraint. A cardinality constraint is introduced in order to limit the number of distinct values of the design variables appearing in any candidate solution. Such constraint is directly enforced when an ant builds a candidate solution, while the other mechanical constraints are handled by means of an adaptive penalty method (APM). The test-problems are composed by structural optimization problems with discrete design variables, and the objectives are to minimize both the structure's weight and its maximum nodal displacement. The Pareto sets generated in the computational experiments are evaluated by means of performance metrics, and the obtained designs are also compared with solutions available from single-objective studies in the literature. (C) 2014 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.

引用

页码：101 / 115

页数：15