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

来源：

COMPUTERS & STRUCTURES | 2012年 / 102卷

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

页码：14 / 27

页数：14

共 22 条

[1]

[Anonymous], 2009, METAHEURISTICS DESIG, DOI DOI 10.1002/9780470496916

[2] A new optimization method: Big Bang Big Crunch [J].