An exact algorithm for finding extreme supported nondominated points of multiobjective mixed integer programs / Özgür Özpeynirci in Management science, Vol. 56 N° 12 (Décembre 2010)  

Public ISBD [article]  inManagement science > Vol. 56 N° 12 (Décembre 2010) . - pp. 2302-2315 Titre : An exact algorithm for finding extreme supported nondominated points of multiobjective mixed integer programs Type de document : texte imprimé Auteurs : Özgür Özpeynirci, Auteur ; Murat Köksalan, Auteur Année de publication : 2011 Article en page(s) : pp. 2302-2315 Note générale : Management Langues : Anglais (eng) Mots-clés : Multiobjective optimization Nondominated points Exact algorithm Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : In this paper, we present an exact algorithm to find all extreme supported nondominated points of multiobjective mixed integer programs. The algorithm uses a composite linear objective function and finds all the desired points in a finite number of steps by changing the weights of the objective functions in a systematic way. We develop further variations of the algorithm to improve its computational performance and demonstrate our algorithm's performance on multiobjective assignment, knapsack, and traveling salesperson problems with three and four objectives. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/cgi/content/abstract/56/12/2302 [article] An exact algorithm for finding extreme supported nondominated points of multiobjective mixed integer programs [texte imprimé] / Özgür Özpeynirci, Auteur ; Murat Köksalan, Auteur . - 2011 . - pp. 2302-2315. Management Langues : Anglais (eng) in Management science > Vol. 56 N° 12 (Décembre 2010) . - pp. 2302-2315 Mots-clés : Multiobjective optimization Nondominated points Exact algorithm Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : In this paper, we present an exact algorithm to find all extreme supported nondominated points of multiobjective mixed integer programs. The algorithm uses a composite linear objective function and finds all the desired points in a finite number of steps by changing the weights of the objective functions in a systematic way. We develop further variations of the algorithm to improve its computational performance and demonstrate our algorithm's performance on multiobjective assignment, knapsack, and traveling salesperson problems with three and four objectives. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/cgi/content/abstract/56/12/2302

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