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An ant colony optimization metaheuristic for single-path multicommodity network flow problems / Li, X. Y. in Journal of the operational research society (JORS), Vol. 61 N° 9 (Septembre 2010) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 61 N° 9 (Septembre 2010) . - pp. 1340–1355 Titre : An ant colony optimization metaheuristic for single-path multicommodity network flow problems Type de document : texte imprimé Auteurs : Li, X. Y., Auteur ; Y. P. Aneja, Auteur ; F. Baki, Auteur Année de publication : 2011 Article en page(s) : pp. 1340–1355 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Networks  and  graphs  Multicommodity  network  flow  Single  path  Routing  strategy  Ant  colony  optimization  Heuristics Index. décimale : 001.424 Résumé : This paper studies the single-path multicommodity network flow problem (SMNF), in which the flow of each commodity can only use one path linking its origin and destination in the network. We study two versions of this problem based on two different objectives. The first version is to minimize network congestion, an issue of concern in traffic grooming over wavelength division multiplexing (WDM), and in which there generally exists a commodity flow between every pair of nodes. The second problem is a constrained version of the general linear multicommodity flow problem, in which, for each commodity, a single path is allowed to send the required flow, and the objective is to determine a flow pattern that obeys the arc capacities and minimizes the total shipping cost. Based on the node-arc and the arc-chain representations, we first present two formulations. Owing to computational impracticality of exact algorithms for practical networks, we propose an ant colony optimization-(ACO) based metaheuristic to deal with SMNF. Considering different problem properties, we devise two versions of ACO metaheuristics to solve these two problems, respectively. The proposed algorithms’ efficiencies are experimentally investigated on some generated instances of SMNF. The test results demonstrate that the proposed ACO metaheuristics are computationally efficient and robust approaches for solving SMNF. DEWEY : 001.424 ISSN : 0361-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n9/abs/jors200986a.html [article] An ant colony optimization metaheuristic for single-path multicommodity network flow problems [texte imprimé] / Li, X. Y., Auteur ; Y. P. Aneja, Auteur ; F. Baki, Auteur . - 2011 . - pp. 1340–1355. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 61 N° 9 (Septembre 2010) . - pp. 1340–1355 Mots-clés : Networks  and  graphs  Multicommodity  network  flow  Single  path  Routing  strategy  Ant  colony  optimization  Heuristics Index. décimale : 001.424 Résumé : This paper studies the single-path multicommodity network flow problem (SMNF), in which the flow of each commodity can only use one path linking its origin and destination in the network. We study two versions of this problem based on two different objectives. The first version is to minimize network congestion, an issue of concern in traffic grooming over wavelength division multiplexing (WDM), and in which there generally exists a commodity flow between every pair of nodes. The second problem is a constrained version of the general linear multicommodity flow problem, in which, for each commodity, a single path is allowed to send the required flow, and the objective is to determine a flow pattern that obeys the arc capacities and minimizes the total shipping cost. Based on the node-arc and the arc-chain representations, we first present two formulations. Owing to computational impracticality of exact algorithms for practical networks, we propose an ant colony optimization-(ACO) based metaheuristic to deal with SMNF. Considering different problem properties, we devise two versions of ACO metaheuristics to solve these two problems, respectively. The proposed algorithms’ efficiencies are experimentally investigated on some generated instances of SMNF. The test results demonstrate that the proposed ACO metaheuristics are computationally efficient and robust approaches for solving SMNF. DEWEY : 001.424 ISSN : 0361-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n9/abs/jors200986a.html