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Solution representation for job shop scheduling problems in ant colony optimisation

Citation

Montgomery, J and Fayad, C and Petrovic, S, Solution representation for job shop scheduling problems in ant colony optimisation, Proceedings of the Fifth International Workshop on Ant Colony Optimization and Swarm Intelligence (ANTS 2006), 4-7 September 2006, Brussels, Belgium, pp. 484-491. ISBN 9783540384823 (2006) [Refereed Conference Paper]


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Copyright Statement

Copyright 2006 Springer-Verlag Berlin Heidelberg

DOI: doi:10.1007/11839088_49

Abstract

Production scheduling problems such as the job shop consist of a collection of operations (grouped into jobs) that must be scheduled for processing on different machines. Typical ant colony optimisation applications for these problems generate solutions by constructing a permutation of the operations, from which a deterministic algorithm can generate the actual schedule. This paper considers an alternative approach in which each machine is assigned a dispatching rule, which heuristically determines the order of operations on that machine. This representation creates a substantially smaller search space that likely contains good solutions. The performance of both approaches is compared on a real-world job shop scheduling problem in which processing times and job due dates are modelled with fuzzy sets. Results indicate that the new approach produces better solutions more quickly than the traditional approach.

Item Details

Item Type:Refereed Conference Paper
Keywords:ant colony optimisation, job shop scheduling, solution representation
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Neural, Evolutionary and Fuzzy Computation
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Information and Computing Sciences
Author:Montgomery, J (Dr James Montgomery)
ID Code:97247
Year Published:2006
Web of Science® Times Cited:8
Deposited By:Information and Communication Technology
Deposited On:2014-12-09
Last Modified:2016-01-19
Downloads:6 View Download Statistics

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