Truss shape optimization using evolutionary ant colony optimization

被引：0

作者：

Hara T. ^{[1
]}

Gan B.S. ^{[2
]}

机构：

[1] Technical Department, Japan Sales Division, MSC Software Ltd

[2] Department of Architecture, Nihon University

来源：

| 1601年 / Architectural Institute of Japan卷 / 82期

关键词：

Evolutionary Structural Optimization; EvolutionaryAnt Colony Optimization; Shape optimization; Truss structure; Ant Colony Optimization;

D O I：

10.3130/aijs.82.1601

中图分类号：

学科分类号：

摘要：

Ant Colony Optimization (ACO) is a multi-Agent approach, and its search process in each cycle is random. Therefore, some design problems can be simulated using the ACO algorithm. Due to its randomness, the ACO is not an efficient approach to obtain a "Rigid" state of structures that usually being the main objective in the structural optimization problems. On the other hand, Evolutionary Structural Optimization (ESO) is a method based on the evolutionary process in nature which is proved to be suitable for solving structural optimization problems. This study proposed a new combined optimization algorithm, called an Evolutionary Ant Colony Optimization (EACO). The EACO is an improvement of the ACO algorithm by using the innovating ESO strategy to solve structural optimization problems. The effectiveness of the proposed EACO is verified by solving shape optimization problems of plane truss examples.

引用

页码：1601 / 1607

页数：6

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