期刊
COMPUTERS & STRUCTURES
卷 81, 期 20, 页码 2003-2009出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0045-7949(03)00253-0
关键词
optimization; genetic algorithm; response surface approximation; composite structure
This paper describes a new approach for reducing the number of the fitness function evaluations required by a genetic algorithm (GA) for optimization problems with mixed continuous and discrete design variables. The proposed additions to the GA make the search more effective and rapidly improve the fitness value from generation to generation. The additions involve memory as a function of both discrete and continuous design variables, multivariate approximation of the fitness function in terms of several continuous design variables, and localized search based on the multivariate approximation. The approximation is demonstrated for the minimum weight design of a composite cylindrical shell with grid stiffeners. (C) 2003 Elsevier Ltd. All rights reserved.
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