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Pheromone modification strategies for ant algorithms applied to dynamic TSP. (English) Zbl 0978.68571
Boers, Egbert J. W. (ed.), Applications of evolutionary computing. Evo Workshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM, Como, Italy, April 18-20, 2001. Proceedings. Berlin: Springer. Lect. Notes Comput. Sci. 2037, 213-222 (2001).
Summary: We investigate strategies for pheromone modification of ant algorithms in reaction to the insertion/deletion of a city of Traveling Salesperson Problem (TSP) instances. Three strategies for pheromone diversification through equalization of the pheromone values on the edges are proposed and compared. One strategy acts globally without consideration of the position of the inserted/deleted city. The other strategies perform pheromone modification only in the neighborhood of the inserted/deleted city, where neighborhood is defined differently for the two strategies. We furthermore evaluate different parameter settings for each of the strategies.
For the entire collection see [Zbl 0960.00056].

MSC:
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
90C59 Approximation methods and heuristics in mathematical programming
90C35 Programming involving graphs or networks
Software:
AntNet
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