InterCriteria Analysis of ACO Start Startegies

Stefka Fidanova, Olympia Roeva, Pawel Gepner, Marcin Paprzycki

DOI: http://dx.doi.org/10.15439/2016F137

Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 547–550 (2016)

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Abstract. In the combinatorial optimization the goal is to find the optimal object from a finite set of objects. From computational point of view the combinatorial optimization problems are hard to be solved. Therefore on this kind of problems usually is applied some metaheuristics. One of the most successful techniques for a lot of classes of problem is metaheuristic algorithm Ant Colony Optimization (ACO). Some start strategies can be applied on ACO algorithms to improve the algorithm performance. In this investigation InterGriteria Analysis (ICrA) is applied on ACO algorithm. On the basis of ICrA we examine and analyse the ACO performance according different start strategies.

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