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Constraint Propagation and Problem Decomposition: A Preprocessing Procedure for the Job Shop Problem

Constraint Propagation and Problem Decomposition: A Preprocessing Procedure for the Job Shop Problem In recent years, constraint propagation techniques have been shown to be highly effective for solving difficult scheduling problems. In this paper, we present an algorithm which combines constraint propagation with a problem decomposition approach in order to simplify the solution of the job shop scheduling problem. This is mainly guided by the observation that constraint propagation is more effective for ‘small’ problem instances. Roughly speaking, the algorithm consists of deducing operation sequences that are likely to occur in an optimal solution of the job shop scheduling problem (JSP). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Operations Research Springer Journals

Constraint Propagation and Problem Decomposition: A Preprocessing Procedure for the Job Shop Problem

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References (44)

Publisher
Springer Journals
Copyright
Copyright © 2002 by Kluwer Academic Publishers
Subject
Business and Management; Operation Research/Decision Theory; Combinatorics; Theory of Computation
ISSN
0254-5330
eISSN
1572-9338
DOI
10.1023/A:1021197120431
Publisher site
See Article on Publisher Site

Abstract

In recent years, constraint propagation techniques have been shown to be highly effective for solving difficult scheduling problems. In this paper, we present an algorithm which combines constraint propagation with a problem decomposition approach in order to simplify the solution of the job shop scheduling problem. This is mainly guided by the observation that constraint propagation is more effective for ‘small’ problem instances. Roughly speaking, the algorithm consists of deducing operation sequences that are likely to occur in an optimal solution of the job shop scheduling problem (JSP).

Journal

Annals of Operations ResearchSpringer Journals

Published: Oct 10, 2004

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