期刊
ENGINEERING OPTIMIZATION
卷 40, 期 9, 页码 789-804出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/03052150802046247
关键词
structural optimization; particle swarm optimization; multiobjective optimization; hybrid technique; sequential linear programming; adaptive weighting coefficient
This article proposes a new multiobjective optimization method for structural problems based on multiobjective particle swarm optimization (MOPSO). A gradient-based optimization method is combined with MOPSO to alleviate constraint-handling difficulties. In this method, a group of particles is divided into two groups - a dominated solution group and a non-dominated solution group. The gradient-based method, utilizing a weighting coefficient method, is applied to the latter to conduct local searching that yields superior non-dominated solutions. In order to enhance the efficiency of exploration in a multiple objective function space, the weighting coefficients are adaptively assigned considering the distribution of non-dominated solutions. A linear optimization problem is solved to determine the optimal weighting coefficients for each non-dominated solution at each iteration. Finally, numerical and structural optimization problems are solved by the proposed method to verify the optimization efficiency.
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