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

delete2012-09-01
delete102
PRE
AI
G
Giada La Scalia *
M
Mario Enea
DOI:10.1016/j.eswa.2012.01.125delete
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摘要

摘要

En 中文
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. (C) 2012 Elsevier Ltd. All rights reserved.
Keyword:
Facility layout problems
Multi objective genetic algorithm
Slicing structure
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期刊

Expert Systems with Applications 封面图
Expert Systems with Applications
IF:
7.5
论文数:
3.0W
被引数:
10.2W

机构

U
University of Palermo
学者数:
1.9W
论文数: 1.5W
被引数: 1.5W
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