Les Inscriptions à la Bibliothèque sont ouvertes en
ligne via le site: https://biblio.enp.edu.dz
Les Réinscriptions se font à :
• La Bibliothèque Annexe pour les étudiants en
2ème Année CPST
• La Bibliothèque Centrale pour les étudiants en Spécialités
A partir de cette page vous pouvez :
Retourner au premier écran avec les recherches... |
Détail de l'auteur
Auteur M. Gumus
Documents disponibles écrits par cet auteur
Affiner la rechercheA single-resource revenue management problem with random resource consumptions / W. Zhuang in Journal of the operational research society (JORS), Vol. 63 N° 9 (Septembre 2012)
[article]
in Journal of the operational research society (JORS) > Vol. 63 N° 9 (Septembre 2012) . - pp. 1213–1227
Titre : A single-resource revenue management problem with random resource consumptions Type de document : texte imprimé Auteurs : W. Zhuang, Auteur ; M. Gumus, Auteur ; D. Zhang, Auteur Année de publication : 2012 Article en page(s) : pp. 1213–1227 Note générale : Operational research Langues : Anglais (eng) Mots-clés : Revenue management Dynamic programming Transportation Index. décimale : 001.424 Résumé : We study a single-resource multi-class revenue management problem where the resource consumption for each class is random and only revealed at departure. The model is motivated by cargo revenue management problems in the airline and other shipping industries. We study how random resource consumption distribution affects the optimal expected profit and identify a preference acceptance order on classes. For a special case where the resource consumption for each class follows the same distribution, we fully characterize the optimal control policy. We then propose two easily computable heuristics: (i) a class-independent heuristic through parameter scaling, and (ii) a decomposition heuristic that decomposes the dynamic programming formulation into a collection of one-dimensional problems. We conduct extensive numerical experiments to investigate the performance of the two heuristics and compared them with several widely studied heuristic policies. Our results show that both heuristics work very well, with class-independent heuristic slightly better between the two. In particular, they consistently outperform heuristics that ignore demand and/or resource consumption uncertainty. Our results demonstrate the importance of considering random resource consumption as another problem dimension in revenue management applications. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n9/abs/jors2011129a.html [article] A single-resource revenue management problem with random resource consumptions [texte imprimé] / W. Zhuang, Auteur ; M. Gumus, Auteur ; D. Zhang, Auteur . - 2012 . - pp. 1213–1227.
Operational research
Langues : Anglais (eng)
in Journal of the operational research society (JORS) > Vol. 63 N° 9 (Septembre 2012) . - pp. 1213–1227
Mots-clés : Revenue management Dynamic programming Transportation Index. décimale : 001.424 Résumé : We study a single-resource multi-class revenue management problem where the resource consumption for each class is random and only revealed at departure. The model is motivated by cargo revenue management problems in the airline and other shipping industries. We study how random resource consumption distribution affects the optimal expected profit and identify a preference acceptance order on classes. For a special case where the resource consumption for each class follows the same distribution, we fully characterize the optimal control policy. We then propose two easily computable heuristics: (i) a class-independent heuristic through parameter scaling, and (ii) a decomposition heuristic that decomposes the dynamic programming formulation into a collection of one-dimensional problems. We conduct extensive numerical experiments to investigate the performance of the two heuristics and compared them with several widely studied heuristic policies. Our results show that both heuristics work very well, with class-independent heuristic slightly better between the two. In particular, they consistently outperform heuristics that ignore demand and/or resource consumption uncertainty. Our results demonstrate the importance of considering random resource consumption as another problem dimension in revenue management applications. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n9/abs/jors2011129a.html