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Candidate set strategies for ant colony optimisation


Randall, M and Montgomery, J, Candidate set strategies for ant colony optimisation, Proceedings of the 3rd International Workshop on Ant Algorithms (ANTS 2002), 12-14 September 2002, Brussels, Belgium, pp. 243-249. ISBN 9783540441465 (2002) [Refereed Conference Paper]

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Copyright Statement

Copyright 2002 Springer-Verlag Berlin Heidelberg

DOI: doi:10.1007/3-540-45724-0_22


Ant Colony Optimisation based solvers systematically scan the set of possible solution elements before choosing a particular one. Hence, the computational time required for each step of the algorithm can be large. One way to overcome this is to limit the number of element choices to a sensible subset, or candidate set. This paper describes some novel generic candidate set strategies and tests these on the travelling salesman and car sequencing problems. The results show that the use of candidate sets helps to find competitive solutions to the test problems in a relatively short amount of time.

Item Details

Item Type:Refereed Conference Paper
Keywords:ant colony optimisation, 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:97259
Year Published:2002
Deposited By:Information and Communication Technology
Deposited On:2014-12-09
Last Modified:2016-01-19
Downloads:335 View Download Statistics

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