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A statistical analysis of parameter values for the rank-based ant colony optimization algorithm for the traveling salesperson problem / Vasko, F. J. in Journal of the operational research society (JORS), Vol. 62 N° 6 (Juin 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 6 (Juin 2011) . - pp. 1169–1176 Titre : A statistical analysis of parameter values for the rank-based ant colony optimization algorithm for the traveling salesperson problem Type de document : texte imprimé Auteurs : Vasko, F. J., Auteur ; Bobeck, J. D., Auteur ; Governale, M. A., Auteur Année de publication : 2011 Article en page(s) : pp. 1169–1176 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Ant  colony  optimization  Combinatorial  optimization  Traveling  salesperson  problem  Statistical  analysis Index. décimale : 001.424 Résumé : Ant colony optimization (ACO) is a metaheuristic for solving combinatorial optimization problems that is based on the foraging behavior of biological ant colonies. Starting with the 1996 seminal paper by Dorigo, Maniezzo and Colorni, ACO techniques have been used to solve the traveling salesperson problem (TSP). In this paper, we focus on a particular type of the ACO algorithm, namely, the rank-based ACO algorithm for the TSP. In particular, this paper identifies an optimal set of key parameters by statistical analysis applied to results of the rank-based ACO for the TSP. Specifically, for six frequently used TSPs available on the World Wide Web, we will solve a total of 27 000 instances for each problem. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n6/abs/jors201074a.html [article] A statistical analysis of parameter values for the rank-based ant colony optimization algorithm for the traveling salesperson problem [texte imprimé] / Vasko, F. J., Auteur ; Bobeck, J. D., Auteur ; Governale, M. A., Auteur . - 2011 . - pp. 1169–1176. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 6 (Juin 2011) . - pp. 1169–1176 Mots-clés : Ant  colony  optimization  Combinatorial  optimization  Traveling  salesperson  problem  Statistical  analysis Index. décimale : 001.424 Résumé : Ant colony optimization (ACO) is a metaheuristic for solving combinatorial optimization problems that is based on the foraging behavior of biological ant colonies. Starting with the 1996 seminal paper by Dorigo, Maniezzo and Colorni, ACO techniques have been used to solve the traveling salesperson problem (TSP). In this paper, we focus on a particular type of the ACO algorithm, namely, the rank-based ACO algorithm for the TSP. In particular, this paper identifies an optimal set of key parameters by statistical analysis applied to results of the rank-based ACO for the TSP. Specifically, for six frequently used TSPs available on the World Wide Web, we will solve a total of 27 000 instances for each problem. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n6/abs/jors201074a.html