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Improving exploration in ant colony optimisation with antennation
conference contribution
posted on 2023-05-23, 08:54 authored by Beer, C, Hendtlass, T, Erin MontgomeryErin MontgomeryAnt Colony Optimisation (ACO) algorithms use two heuristics to solve computational problems: one long-term (pheromone) and the other short-term (local heuristic). This paper details the development of antennation, a mid-term heuristic based on an analogous process in real ants. This is incorporated into ACO for the Travelling Salesman Problem (TSP). Antennation involves sharing information of the previous paths taken by ants, including information gained from previous meetings. Antennation was added to the Ant System (AS), Ant Colony System (ACS) and Ant Multi-Tour System (AMTS) algorithms. Tests were conducted on symmetric TSPs of varying size. Antennation provides an advantage when incorporated into algorithms without an inbuilt exploration mechanism and a disadvantage to those that do. AS and AMTS with antennation have superior performance when compared to their canonical form, with the effect increasing as problem size increases.
History
Publication title
Proceedings of the 2012 IEEE Congress on Evolutionary ComputationPagination
2926-2933ISBN
978-1-4673-1510-4Department/School
School of Information and Communication TechnologyPublisher
Curran Associates, IncPlace of publication
United States of AmericaEvent title
WCCI 2012 IEEE World Congress on Computational IntelligenceEvent Venue
Brisbane, AustraliaDate of Event (Start Date)
2012-06-10Date of Event (End Date)
2012-06-15Rights statement
Copyright 2012 IEEERepository Status
- Restricted