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| A convergence speed study on evolutionary algorithms for solving truss multi-objective topology optimization |
| Received:April 04, 2014 Revised:June 25, 2014 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx201503002 |
| KeyWord:evolutionary algorithm convergence speed truss topology optimization multi-objective optimization stress constraint |
| Author | Institution |
| 胡浩 |
大连理工大学 工程力学系 工业装备结构分析国家重点实验室, 大连 ;盐城工学院 土木工程学院, 盐城 |
| 李刚 |
大连理工大学 工程力学系 工业装备结构分析国家重点实验室, 大连 |
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| Abstract: |
| Though evolutionary algorithms (EAs) are capable of satisfying the demands arising from the new advancements in structural topology optimization on global optimization,black-box function optimization,combinatorial optimization and multi-objective optimization,the necessity of applying them to this field still depends on their convergence and computational efficiency simultaneously.This paper aims to reveal competent algorithms on these two aspects for stress constrained truss multi-objective topology optimization (MOTO) problems.We first propose a general method tailor-made for examining the convergence and efficiency of EAs on solving MOTO.The global optima of typical MOTO problems are rigorously derived using enumeration.Then multi-level convergence criteria are defined using hypervolume metric.The comparative study reveals outstanding EAs with greatest convergence speeds under different convergence requirement and the corresponding algorithmic mechanism.This way,this paper not only contributes to the theoretical foundation of solving MOTO problems using EAs,but also provides support for high efficiently solving practical engineering topology optimization problems. |