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2012•Applied Mechanics and MaterialsOpen access

Complex Genetic Algorithm for Structure Shape Optimization Design of Mixed Discrete Variables

Chao Yan Zhu, Jingyu Liu, Hong Yan Liu, Xue Zhi Wang

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Abstract

Discrete complex method is used in genetic algorithm(GA) and a mixed genetic algorithm called complex genetic algorithm(CGA) is formed. The complex method used here increases the quality of species groups, and improves the searching efficiency. The mixed genetic algorithm method is used in the shape optimization for mixed discrete variables. The integration and coding of the shape variables and the cross-section variables in genetic algorithm can not only solve the coupling problem of two kinds of variables, but also avoid the partial optimum solution resulting from the separation of the two kinds of variables. The result of the exemplification indicates that the complex genetic algorithm for structure shape optimization design of mixed discrete variables is effective.

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What this paper is about

Discrete complex method is used in genetic algorithm(GA) and a mixed genetic algorithm called complex genetic algorithm(CGA) is formed. The complex method used here increases the quality of species groups, and improves the searching efficiency. The mixed genetic algorithm method is used in the shape optimization for mixed discrete variables. The integration and coding of the shape variables and the cross-section variables in genetic algorithm can not only solve the coupling problem of two kinds of variables, but also avoid the partial optimum solution resulting from the separation of the two kinds of variables. The result of the exemplification indicates that the complex genetic algorithm for structure shape optimization design of mixed discrete variables is effective.

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Available abstract

Discrete complex method is used in genetic algorithm(GA) and a mixed genetic algorithm called complex genetic algorithm(CGA) is formed. The complex method used here increases the quality of species groups, and improves the searching efficiency. The mixed genetic algorithm method is used in the shape optimization for mixed discrete variables. The integration and coding of the shape variables and the cross-section variables in genetic algorithm can not only solve the coupling problem of two kinds of variables, but also avoid the partial optimum solution resulting from the separation of the two kinds of variables. The result of the exemplification indicates that the complex genetic algorithm for structure shape optimization design of mixed discrete variables is effective.

Key concepts: Genetic algorithm, Algorithm, Population-based incremental learning, Meta-optimization, Mathematics, Mathematical optimization, Coding (social sciences), Computer science

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