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