کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
511808 | 865921 | 2009 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A genetic algorithm with memory for mixed discrete–continuous design optimization
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
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چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Structures - Volume 81, Issue 20, August 2003, Pages 2003–2009
Journal: Computers & Structures - Volume 81, Issue 20, August 2003, Pages 2003–2009
نویسندگان
Vladimir B. Gantovnik, Christine M. Anderson-Cook, Zafer Gürdal, Layne T. Watson,