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Aspirational preferences and their representation by risk measures / Brown, David B. in Management science, Vol. 58 N° 11 (Novembre 2012) 

Public ISBD [article]  in Management science > Vol. 58 N° 11 (Novembre 2012) . - pp. 2095-2113 Titre : Aspirational preferences and their representation by risk measures Type de document : texte imprimé Auteurs : Brown, David B., Auteur ; Enrico De Giorgi, Auteur ; Melvyn Sim, Auteur Année de publication : 2013 Article en page(s) : pp. 2095-2113 Note générale : Management Langues : Anglais (eng) Mots-clés : Representation  of  choice  Risk  measures  Aspiration  levels  Decision  theory  paradoxes Résumé : We consider choice over uncertain, monetary payoffs and study a general class of preferences. These preferences favor diversification, except perhaps on a subset of sufficiently disliked acts over which concentration is instead preferred. This structure encompasses a number of known models (e.g., expected utility and several variants under a concave utility function). We show that such preferences share a representation in terms of a family of measures of risk and targets. Specifically, the choice function is equivalent to selection of a maximum index level such that the risk of beating the target at that level is acceptable. This representation may help to uncover new models of choice. One that we explore in detail is the special case when the targets are bounded. This case corresponds to a type of satisficing and has descriptive relevance. Moreover, the model is amenable to large-scale optimization. ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/58/11/2095.abstract [article] Aspirational preferences and their representation by risk measures [texte imprimé] / Brown, David B., Auteur ; Enrico De Giorgi, Auteur ; Melvyn Sim, Auteur . - 2013 . - pp. 2095-2113. Management Langues : Anglais (eng) in Management science > Vol. 58 N° 11 (Novembre 2012) . - pp. 2095-2113 Mots-clés : Representation  of  choice  Risk  measures  Aspiration  levels  Decision  theory  paradoxes Résumé : We consider choice over uncertain, monetary payoffs and study a general class of preferences. These preferences favor diversification, except perhaps on a subset of sufficiently disliked acts over which concentration is instead preferred. This structure encompasses a number of known models (e.g., expected utility and several variants under a concave utility function). We show that such preferences share a representation in terms of a family of measures of risk and targets. Specifically, the choice function is equivalent to selection of a maximum index level such that the risk of beating the target at that level is acceptable. This representation may help to uncover new models of choice. One that we explore in detail is the special case when the targets are bounded. This case corresponds to a type of satisficing and has descriptive relevance. Moreover, the model is amenable to large-scale optimization. ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/58/11/2095.abstract

Robust storage assignment in unit-load warehouses / Marcus Ang in Management science, Vol. 58 N° 11 (Novembre 2012) 

Public ISBD [article]  in Management science > Vol. 58 N° 11 (Novembre 2012) . - pp. 2114-2130 Titre : Robust storage assignment in unit-load warehouses Type de document : texte imprimé Auteurs : Marcus Ang, Auteur ; Yun Fong Lim, Auteur ; Melvyn Sim, Auteur Année de publication : 2013 Article en page(s) : pp. 2114-2130 Note générale : Management Langues : Anglais (eng) Mots-clés : Inventory  Production  Uncertainty  Programming  Linear  Large  scale  systems  Transportation  Materials  handling Résumé : Assigning products to and retrieving them from proper storage locations are crucial decisions in minimizing the operating cost of a unit-load warehouse. The problem becomes intractable when the warehouse faces variable supply and uncertain demand in a multiperiod setting. We assume a factor-based demand model in which demand for each product in each period is affinely dependent on some uncertain factors. The distributions of these factors are only partially characterized. We introduce a robust optimization model that minimizes the worst-case expected total travel in the warehouse with distributional ambiguity of demand. Under a linear decision rule, we obtain a storage and retrieval policy by solving a moderate-size linear optimization problem. Surprisingly, despite imprecise specification of demand distributions, our computational studies suggest that the linear policy achieves close to the expected value given perfect information and significantly outperforms existing heuristics in the literature. ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/58/11/2114.abstract [article] Robust storage assignment in unit-load warehouses [texte imprimé] / Marcus Ang, Auteur ; Yun Fong Lim, Auteur ; Melvyn Sim, Auteur . - 2013 . - pp. 2114-2130. Management Langues : Anglais (eng) in Management science > Vol. 58 N° 11 (Novembre 2012) . - pp. 2114-2130 Mots-clés : Inventory  Production  Uncertainty  Programming  Linear  Large  scale  systems  Transportation  Materials  handling Résumé : Assigning products to and retrieving them from proper storage locations are crucial decisions in minimizing the operating cost of a unit-load warehouse. The problem becomes intractable when the warehouse faces variable supply and uncertain demand in a multiperiod setting. We assume a factor-based demand model in which demand for each product in each period is affinely dependent on some uncertain factors. The distributions of these factors are only partially characterized. We introduce a robust optimization model that minimizes the worst-case expected total travel in the warehouse with distributional ambiguity of demand. Under a linear decision rule, we obtain a storage and retrieval policy by solving a moderate-size linear optimization problem. Surprisingly, despite imprecise specification of demand distributions, our computational studies suggest that the linear policy achieves close to the expected value given perfect information and significantly outperforms existing heuristics in the literature. ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/58/11/2114.abstract