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An Improved Integer Coded Genetic Algorithm for Discrete Optimization of Structures

Ling Zhang

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Abstract

In this paper, an improved integer coded genetic algorithm is presented for discrete optimization of structures. It takes (-1,0,1) programming operator to expand the ability of local searching and presents a strategy to choose the starting point of (-1,0,1) programming operator. It also presents a restriction punish gene to discriminate the phenomenon of the same fitness for different combinations. The result of an example shows that this algorithm converges to the best solution quite quickly.

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What this paper is about

In this paper, an improved integer coded genetic algorithm is presented for discrete optimization of structures. It takes (-1,0,1) programming operator to expand the ability of local searching and presents a strategy to choose the starting point of (-1,0,1) programming operator. It also presents a restriction punish gene to discriminate the phenomenon of the same fitness for different combinations. The result of an example shows that this algorithm converges to the best solution quite quickly.

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Available abstract

In this paper, an improved integer coded genetic algorithm is presented for discrete optimization of structures. It takes (-1,0,1) programming operator to expand the ability of local searching and presents a strategy to choose the starting point of (-1,0,1) programming operator. It also presents a restriction punish gene to discriminate the phenomenon of the same fitness for different combinations. The result of an example shows that this algorithm converges to the best solution quite quickly.

Key concepts: Integer programming, Operator (biology), Mathematical optimization, Algorithm, Integer (computer science), Genetic algorithm, Genetic programming, Discrete optimization

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