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Efficient reallocation under additive and responsive preferences

Aziz, Haris; Biro, Peter; Lang, Jérôme; Lesca, Julien; Monnot, Jérôme (2019), Efficient reallocation under additive and responsive preferences, Theoretical Computer Science, 790, p. 1-15. 10.1016/j.tcs.2019.05.011

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157002248340619.pdf (289.9Kb)
Type
Article accepté pour publication ou publié
Date
2019
Journal name
Theoretical Computer Science
Volume
790
Publisher
Elsevier
Pages
1-15
Publication identifier
10.1016/j.tcs.2019.05.011
Metadata
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Author(s)
Aziz, Haris
University of South Wales
Biro, Peter
Institute of Economics
Lang, Jérôme
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Lesca, Julien
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Monnot, Jérôme cc
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
Reallocating resources to get mutually beneficial outcomes is a fundamental problem in various multi-agent settings. While finding an arbitrary Pareto optimal allocation is generally easy, checking whether a particular allocation is Pareto optimal can be much more difficult. This problem is equivalent to checking that the allocated objects cannot be reallocated in such a way that at least one agent prefers her new allocation to her old one, and no agent prefers her old allocation to her new one. We consider the problem for two related types of preference relations over sets of objects. In the first part of the paper we focus on the setting in which agents express additive cardinal utilities over objects. We present computational hardness results as well as polynomial-time algorithms for testing Pareto optimality under different restrictions such as two utility values or lexicographic utilities. In the second part of the paper we assume that agents express only their (ordinal) preferences over individual objects, and that their underlying preferences are additively separable. In this setting, we present characterizations and polynomial-time algorithms for possible and necessary Pareto optimality.
Subjects / Keywords
Fair division; Resource allocation; Pareto optimality

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