Chapter

Ant Algorithms

Volume 2463 of the series Lecture Notes in Computer Science pp 243-249

Date:

Candidate Set Strategies for Ant Colony Optimisation

  • Marcus RandallAffiliated withSchool of Information Technology, Bond University Gold Coast
  • , James MontgomeryAffiliated withSchool of Information Technology, Bond University Gold Coast

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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.