改進的多目標遺傳算法在結構優(yōu)化設計中的應用[001](參考版)
2025-06-19 12:40本頁面
【正文】 參考文獻1 陳國良 等.《遺傳算法及其應用》. 人民郵電出版社2 劉勇 等.《非數值并行算法遺傳算法》. 科學出版社3 [日]玄光南.《遺傳算法與工程設計》. 科學出版社4 Kirsch,U. Optimal structural :McGrawhill,19815 Eschenaure,H,Koski,J and Osycka,A. Multicriteria Design Optimization. New York SpringerVerlag, 19906 David Veldhuizen and Gray B. Lamont. Multiobjective Evolutionary Algorithm Research: A History and Analysis. October 14,19987 Colors M. Fonseca and Peter J. Fleming. A Overview of Evolutionary Algorithms in Multiobjective Optimization. May 19,19958 Eckart Zitzler. Evolutionary Algorithm for Multiobjective Optimization,Methods and Applications. November 11,19999 Shigeru Obayashi,Daisuke Sasaki,Yukihiro Takeguchi,and Naoki Hirose. Multiobjective Evolutionary Computation for Supersonic Wingshape Optimization10 David Todd and Pratyush Sen. Distributed Task Scheduling And Allocation Using Genetic Algorithms. October, 199811 ,. Supervised parallel genetic algorithms in Aerodynamic optimization, in 13th AIAA CFD Conference,AIAA paper97’1852, American Institute of Aeronautics and Astronautics (AIAA). Snowmass Co., ., June 1997. 12 D. Quagliarella, A. Vicini. Coupling Genetic Algorithms and Gradient Based Optimization Techniques, in Quagliarella D. et al., editors, Genetic Algorithms and Evolution Strategies in Engineering and Computer Science. John Wiley amp。盡管采用了許多改進機制，對于不同的問題仍然沒有一個通用的、魯棒性強的算法來求解多目標優(yōu)化問題，本文的算法也依賴于問題本身的特性。這樣可以保證父代的優(yōu)異特性大部分能傳到子
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