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A multi objective genetic algorithm for the facility layout problem based upon slicing structure encoding

机译:基于切片结构编码的设施布局问题多目标遗传算法

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摘要

This paper proposes a new multi objective genetic algorithm (MOGA) for solving unequal area facility layout problems (UA-FLPs). The genetic algorithm suggested is based upon the slicing structure where the relative locations of the facilities on the floor are represented by a location matrix encoded in two chromosomes. A block layout is constructed by partitioning the floor into a set of rectangular blocks using guillotine cuts satisfying the areas requirements of the departments. The procedure takes into account four objective functions (material handling costs, aspect ratio, closeness and distance requests) by means of a Pareto based evolutionary approach. The main advantage of the proposed formulation, with respect to existing referenced approaches (e.g. bay structure), is that the search space is considerably wide and the practicability of the layout designs is preserved, thus improving the quality of the solutions obtained.
机译:本文提出了一种新的多目标遗传算法(MOGA),用于解决不等面积的设施布局问题(UA-FLP)。提出的遗传算法基于切片结构,其中设施在地板上的相对位置由编码在两个染色体中的位置矩阵表示。通过使用断头台切工将地板分成一组矩形块来构造块布局,以满足部门的面积要求。该程序通过基于Pareto的进化方法考虑了四个目标功能(物料处理成本,长宽比,亲密性和距离请求)。相对于现有参考方法(例如,海湾结构),所提出的公式的主要优点是搜索空间相当宽,并且保留了布局设计的实用性,从而提高了所获得解决方案的质量。

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