DocumentCode :
952406
Title :
Managing genetic search in job shop scheduling
Author :
Uckun, Serdar ; Bagchi, Sugato ; Kawamura, Kazuhiko ; Miyabe, Yutaka
Author_Institution :
Vanderbilt Univ., Nashville, TN, USA
Volume :
8
Issue :
5
fYear :
1993
Firstpage :
15
Lastpage :
24
Abstract :
The Vanderbilt Schedule Optimizer Prototype (VSOP), which uses genetic algorithms as search methods for job shop scheduling problems, is discussed. A job shop is a facility that produces goods according to prespecified process plans, under several domain-dependent and common sense constraints. The scheduling of orders in a job shop is a multifaceted problem. VSOP uses domain-specific chromosome representations, recombination operators, and local enumerative search to increase efficiency. Experimental results from a fully implemented VSOP package are presented.<>
Keywords :
genetic algorithms; manufacturing data processing; scheduling; search problems; VSOP; Vanderbilt Schedule Optimizer Prototype; common sense constraints; domain-specific chromosome representations; genetic algorithms; job shop scheduling problems; local enumerative search; multifaceted problem; prespecified process plans; recombination operators; search methods; Artificial intelligence; Genetics; Job shop scheduling; Metals industry; Operations research; Optimal scheduling; Optimization methods; Polynomials; Search methods; Steel;
fLanguage :
English
Journal_Title :
IEEE Expert
Publisher :
ieee
ISSN :
0885-9000
Type :
jour
DOI :
10.1109/64.236477
Filename :
236477
Link To Document :
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