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Contribution to Book
Candidate set strategies for ant colony optimisation
Lecture Notes in Computer Science: Ant Algorithms (2002)
  • Marcus Randall, Bond University
  • James Montgomery, Bond University
Abstract

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.

Keywords
  • candidate,
  • set,
  • strategies,
  • ant,
  • colony,
  • optimisation
Publication Date
January 1, 2002
Publisher
Springer-Verlag
Publisher Statement
Interim status: Citation only.

Randall, M., & Montgomery, J. Candidate set strategies for ant colony optimisation. Ant Algorithms. Proceedings of the 3rd International Workshop on Ant Algorithms (ANTS 2002). Brussels, Belgium, 12-14 September 2002. Published in Lecture Notes in Computer Science: Ant Algorithms, Vol. 2463, pp. 243-249.

Access the publisher's website.

2002 HERDC submission.

© Copyright Springer-Verlag Berlin Heidelberg 2002

Citation Information
Marcus Randall and James Montgomery. "Candidate set strategies for ant colony optimisation" Lecture Notes in Computer Science: Ant Algorithms Vol. 2463 (2002)
Available at: http://works.bepress.com/marcus_randall/30/