NDLI: Part-machine family formation using genetic algorithms in a fuzzy environment

Content Provider	Springer Nature Link
Author	Pai, Ping Feng Chang, Ping Teng Lee, Shi Yin
Copyright Year	2004
Abstract	In traditional cell-formation problems, it is assumed that each part is developed on a single machine. However, in many realistic situations, the suitability of alternative machines for developing the same part feature is frequently vague. Therefore, the fuzzy relation is ideally suited to represent this vague and uncertain cell-formation problem. Furthermore, part-machine family formation problems are usually NP-complete. In this study, a genetic algorithm (GA) is used to deal with the problem. The aim of this study is to design a GA-based algorithm to solve the part-machine family formation problem in a fuzzy environment. The results of computational tests presented are very promising.
Starting Page	1175
Ending Page	1179
Page Count	5
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	25
Issue Number	11-12
e-ISSN	14333015
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2004-02-20
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Fuzzy set theory Genetic algorithms Part-machine family formation Industrial and Production Engineering Production Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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