期刊
ENGINEERING OPTIMIZATION
卷 36, 期 5, 页码 585-605出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/03052150410001704854
关键词
evolutionary algorithms; particle swarm optimization; constrained optimization; mechanical design
This paper presents an improved particle swarm optimizer (PSO) for solving mechanical design optimization problems involving problem-specific constraints and mixed variables such as integer, discrete and continuous variables. A constraint handling method called the 'fly-back mechanism' is introduced to maintain a feasible population. The standard PSO algorithm is also extended to handle mixed variables using a simple scheme. Five benchmark problems commonly used in the literature of engineering optimization and nonlinear programming are successfully solved by the proposed algorithm. The proposed algorithm is easy to implement, and the results and the convergence performance of the proposed algorithm are better than other techniques.
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