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Application of genetic algorithm model in optimal layout of rectangular part

Xiaozhen Mi

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Abstract

To improve the utilization ratio of stock sheets and reduce the cost of production,the genetic algorithm was adopted to optimize the problem of rectangular part optimal layout on stock sheets.The model of genetic algorithm and the design method of the genetic operators was eslablished.Genetic algorithm model was applied in rectangular part op- timal layout combined with the lowest horizontal line-search algorithm.The experiment results are satisfied with the technical requirements ofall the sameand laying the same rectangular part together,and the utilization ratio of stock sheets is about 94%.This method can be used in practice.

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What this paper is about

To improve the utilization ratio of stock sheets and reduce the cost of production,the genetic algorithm was adopted to optimize the problem of rectangular part optimal layout on stock sheets.The model of genetic algorithm and the design method of the genetic operators was eslablished.Genetic algorithm model was applied in rectangular part op- timal layout combined with the lowest horizontal line-search algorithm.The experiment results are satisfied with the technical requirements ofall the sameand laying the same rectangular part together,and the utilization ratio of stock sheets is about 94%.This method can be used in practice.

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Available abstract

To improve the utilization ratio of stock sheets and reduce the cost of production,the genetic algorithm was adopted to optimize the problem of rectangular part optimal layout on stock sheets.The model of genetic algorithm and the design method of the genetic operators was eslablished.Genetic algorithm model was applied in rectangular part op- timal layout combined with the lowest horizontal line-search algorithm.The experiment results are satisfied with the technical requirements ofall the sameand laying the same rectangular part together,and the utilization ratio of stock sheets is about 94%.This method can be used in practice.

Key concepts: Genetic algorithm, Stock (firearms), Algorithm, Mathematical optimization, Computer science, Engineering, Mathematics, Mechanical engineering

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