改進(jìn)的多目標(biāo)遺傳算法在結(jié)構(gòu)優(yōu)化設(shè)計(jì)中的應(yīng)用[001]-資料下載頁(yè)
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【正文】 g 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。 Sons Ltd., England, Nov. 1997, pp. 289309. 13 A. Vicini, D. Quagliarella. Inverse and Direct Airfoil Design Using a Multiobjective Genetic Algorithm. AIAA Journal, Vol. 35, No. 9, Sep. 1997, pp. 14991505. AN IMPROVING MULTIOBJECTIVE GENETIC ALGORITHMS FOR STRUCTURAL OPTIMIZATIONGuanzhihua ( University 9013 POBOX Tianjin 300072)Wanjie(School of Management of Hebei university Tianjian 300000)Abstract This paper discusses some problems of Multiobjective Genetic Algorithms(MOGAs) at the same time , gives some new improvements to MOGAs. These improvements include: niche, stopping criteria, filtering, mating restrictions, the use of objective constriction. By using these technical, we can overe the shortings in niche formation, algorithms stopping and so on. At last, we give two structural designing optimal examples, which use this algorithm.Keywords Multiobjective , Genetic Algorithms , design optimization.
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