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A Parallel Genetic Algorithm for the Geometrically Constrained Site Layout Problem with Unequal-Size Facilities

机译:设施不等的几何约束站点布局问题的并行遗传算法

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摘要

Parallel genetic algorithms techniques have been used in a variety of computer engineering and science areas. This paper presents a parallel genetic algorithm to solve the site layout problem with unequal-size and constrained facilities. The problem involves coordinating the use of limited space to accommodate temporary facilities subject to geometric constraints. The problem is characterised by affinity weights used to model transportation costs between facilities, and by geometric constraints between relative positions of facilities on site. The algorithm is parallelised based on a message passing SPMD architecture using parallel search and chromosomes migration. The algorithm is tested on a variety of layout problems to illustrate its performance. In specific, in the case of: (1) loosely versus tightly constrained layouts with equal levels of interaction between facilities, (2) loosely versus tightly packed layouts with variable levels of interactions between facilities, and (3) loosely versus tightly constrained layouts. Favorable results are reported.
机译:并行遗传算法技术已用于各种计算机工程和科学领域。本文提出了一种并行遗传算法来解决规模不等,设施受限的站点布局问题。问题在于协调有限空间的使用,以适应受几何约束的临时设施。该问题的特征在于用于对设施之间的运输成本进行建模的亲和力权重,以及设施在现场的相对位置之间的几何约束。该算法基于使用并行搜索和染色体迁移的消息传递SPMD体系结构进行并行化。在各种布局问题上对该算法进行了测试,以说明其性能。具体而言,在以下情况下:(1)设施之间交互程度相同的宽松布局与严格约束布局;(2)设施之间交互程度不同的宽松布局与紧密布局;以及(3)宽松布局与紧密约束布局。报告了良好的结果。

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