Application of genetic algorithm for rectangular object layout optimization
Xiaozhen Mi, Xiaodong Zhao, Wenzhong Zhao, Wenhui Fan
Abstract
Xiaozhen Mi, Xiaodong Zhao, Wenzhong Zhao, Wenhui Fan
Abstract
Rectangular object layout is not a simple NP (nondeterministic polynomial) optimization problem because of the practical production rules, such as guillotine. Under some situations, the guillotine is even more important than the pure using ratio of metal sheets. To improve the using ratio of stock sheets and to reduce the production costs, the genetic algorithm is adopted to optimize rectangular object layout on stock sheets. The purpose of this paper is to construct the model of genetic algorithm and design the genetic operators. Combined with the lowest horizontal line- search algorithm, genetic algorithm model is applied into rectangular object layout optimization. Results show that the model in the paper can satisfy not only the practical production requirements of guillotine, but also the requirement for production convenience. In this way, user can get optimal layout results effectively and quickly and a higher material using ratio at the same time for normal production practice.
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Rectangular object layout is not a simple NP (nondeterministic polynomial) optimization problem because of the practical production rules, such as guillotine. Under some situations, the guillotine is even more important than the pure using ratio of metal sheets. To improve the using ratio of stock sheets and to reduce the production costs, the genetic algorithm is adopted to optimize rectangular object layout on stock sheets. The purpose of this paper is to construct the model of genetic algorithm and design the genetic operators. Combined with the lowest horizontal line- search algorithm, genetic algorithm model is applied into rectangular object layout optimization. Results show that the model in the paper can satisfy not only the practical production requirements of guillotine, but also the requirement for production convenience. In this way, user can get optimal layout results effectively and quickly and a higher material using ratio at the same time for normal production practice.
Key concepts: Genetic algorithm, Computer science, Nondeterministic algorithm, Mathematical optimization, Object (grammar), Production line, Production (economics), Algorithm