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Structural advantages for ant colony optimisation inherent in permutation scheduling problems
Citation
Montgomery, J and Randall, M and Hendtlass, T, Structural advantages for ant colony optimisation inherent in permutation scheduling problems, Proceedings of the 18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2005), 22-24 June 2005, Bari, Italy, pp. 218-228. ISBN 978-3-540-26551-1 (2005) [Refereed Conference Paper]
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Copyright Statement
Copyright 2005 Springer-Verlag Berlin Heidelberg
Abstract
When using a constructive search algorithm, solutions to scheduling problems such as the job shop and open shop scheduling problems are typically represented as permutations of the operations to be scheduled. The combination of this representation and the use of a constructive algorithm introduces a bias typically favouring good solutions. When ant colony optimisation is applied to these problems, a number of alternative pheromone representations are available, each of which interacts with this underlying bias in different ways. This paper explores both the structural aspects of the problem that introduce this underlying bias and the ways two pheromone representations may either lead towards poorer or better solutions over time. Thus it is a synthesis of a number of recent studies in this area that deal with each of these aspects independently.
Item Details
Item Type: | Refereed Conference Paper |
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Keywords: | ant colony optimisation, scheduling problems, solution representation, search space, optimisation |
Research Division: | Information and Computing Sciences |
Research Group: | Machine learning |
Research Field: | Neural networks |
Objective Division: | Expanding Knowledge |
Objective Group: | Expanding knowledge |
Objective Field: | Expanding knowledge in the information and computing sciences |
UTAS Author: | Montgomery, J (Dr James Montgomery) |
ID Code: | 97249 |
Year Published: | 2005 |
Web of Science® Times Cited: | 5 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2014-12-09 |
Last Modified: | 2016-01-19 |
Downloads: | 4 View Download Statistics |
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