トラス構造物重量最適化のための効率的な遺伝的アルゴリズムの開発

概要

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This paper presents a new efficient genetic algorithm for truss structure optimization. In many optimum design problems, values of design valiables are real numbers. We have proposed the "Center Neighborhood Crossover (CNX)" for real coded genetic algorithms. CNX is a powerful tool for function optimizations. Since it is uncertain that these operators are able to work for practical design problems efficiently, it is necessary to examine some crossover operators for practical use. In the present study, we verified and compared the performance of several crossover operators using benchmark functions. Furthermore, we tried to optimize a truss structure problem using these operators. By considering the results mentioned above, we developed the "two-stage method" for truss structure optimization. This method bring us the efficient search and the high-accurate optimum solution.
一般社団法人日本機械学会の論文
2001-08-25