eCite Digital Repository
Candidate set strategies for ant colony optimisation
Citation
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]
 | PDF (Author's final draft (probably called post-print by some publishers)) 157Kb |
Copyright Statement
Copyright 2002 Springer-Verlag Berlin Heidelberg
DOI: doi:10.1007/3-540-45724-0_22
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.
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: | 321 View Download Statistics |
Repository Staff Only: item control page