Title

Improving the Performance of MAX-MIN Ant System on the TSP Using Stubborn Ants

Abstract

In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stochastically generates its candidate solution, in a given iteration, based on the same pheromone τ and heuristic η information as every other ant. Stubborn ants is an ACO variation in which if an ant generates a particular candidate solution in a given iteration, then the components of that solution will have a higher probability of being selected in the candidate solution generated by that ant in the next iteration. We evaluate this variation in the context of MAX-MIN Ant System using 41 instances of the Traveling Salesman Problem (TSP), and find that it improves solution quality to a statistically-significant extent.

Meeting Name

14th International Conference on Genetic and Evolutionary Computation, GECCO'12 (2012: Jul. 7-11, Philadelphia, PA)

Department(s)

Electrical and Computer Engineering

International Standard Book Number (ISBN)

9781450311786

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2012 Association for Computing Machinery (ACM), All rights reserved.


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