Search Context Awareness in Several Ant Colony Optimization Models
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 t and heuristic η information as every other ant. Stubborn ants are a variation in which each ant is sensitive to the context of its own personal search history. Specifically, 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 the Traveling Salesman Problem (TSP), finding that it can both improve the quality of the solution and reduce execution-time.
A. M. Abdelbar and D. C. Wunsch, "Search Context Awareness in Several Ant Colony Optimization Models," International Journal of Computers and their Applications, vol. 20, no. 2, pp. 97-110, International Society for Computers and Their Applications (ISCA), Jan 2013.
Electrical and Computer Engineering
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