Truss optimization with natural frequency constraints using a hybridized CSS-BBBC algorithm with trap recognition capability

被引:129
作者
Kaveh, A. [1 ]
Zolghadr, A. [1 ]
机构
[1] Iran Univ Sci & Technol, Sch Civil Engn, Ctr Excellence Fundamental Studies Struct Engn, Tehran 16, Iran
基金
美国国家科学基金会;
关键词
Frequency constraint structural optimization; Hybridization; Charged System Search and the Big Bang-Big Crunch (CSS-BBBC); Truss structures; STRUCTURAL OPTIMIZATION; SEARCH;
D O I
10.1016/j.compstruc.2012.03.016
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Frequency constraint structural optimization includes the exploration of highly nonlinear and non-convex search spaces with several local optima. These characteristics of the search spaces increase the possibility of the agents getting trapped in a local optimum, when using a meta-heuristic algorithm. In this paper a diversity index is introduced which together with a few other criteria, can be employed to recognize such traps. By the use of these concepts, a hybridization of the Charged System Search and the Big Bang-Big Crunch algorithms with trap recognition capability is proposed. Five numerical examples are considered to demonstrate the efficiency of the algorithm. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:14 / 27
页数:14
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