arrow
Return

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
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

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.
Keywords:
Facility layout problems
Multi objective genetic algorithm
Slicing structure
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Expert Systems with Applications cover
Expert Systems with Applications
IF:
7.5
Papers:
3.0W
Citations:
10.2W

Organization

U
University of Palermo
Scholars:
1.9W
Papers: 1.5W
Citations: 1.5W
Cited Papers

Cited Papers

The role of acoustic phonons for Rabi oscillations in semiconductor quantum dots
err2005-11-03
err0
PREAI
errA. Krügel; V.M. Axt; T. Kuhn; P. Machnikowski; A. Vagov
errShare
errSave
Solving facility layout problems with strict geometric constraints using a two-phase genetic algorithm
err2008-12-04
err19
errOAAI
errDiego-Mas, J. A.; Santamarina-Siurana, M. C.; Alcaide-Marzal, J.; Cloquell-Ballester, V. A.
errShare
errSave
researcher View more