On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Stochastic dominance and expected utility: survey and analysis
Management Science
A Constraint Programming Approach to the Stable Marriage Problem
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Negotiating over small bundles of resources
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Undominated VCG redistribution mechanisms
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Efficiency and envy-freeness in fair division of indivisible goods
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
An axiomatic approach to robustness in search problems with multiple scenarios
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
LP Solvable Models for Multiagent Fair Allocation Problems
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Bicriteria models for fair and efficient resource allocation
SocInfo'10 Proceedings of the Second international conference on Social informatics
Preferences in AI: An overview
Artificial Intelligence
Lorenz versus Pareto dominance in a single machine scheduling problem with rejection
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
Reduction of economic inequality in combinatorial domains
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Hi-index | 0.00 |
This paper deals with fair assignment problems in decision contexts involving multiple agents. In such problems, each agent has its own evaluation of costs and we want to find a fair compromise solution between individual point of views. Lorenz dominance is a standard decision model used in Economics to refine Pareto dominance while favoring solutions that fairly share happiness among agents. In order to enhance the discrimination possibilities offered by Lorenz dominance, we introduce here a new model called infinite order Lorenz dominance. We establish a representation result for this model using an ordered weighted average with decreasing weights. Hence we exhibit some properties of infinite order Lorenz dominance that explain how fairness is achieved in the aggregation of individual preferences. Then we explain how to solve fair assignment problems of m items to n agents, using infinite order Lorenz dominance and other models used for measuring inequalities. We show that this problem can be reformulated as a 0--1 non-linear optimization problems that can be solved, after a linearization step, by standard LP solvers. We provide numerical results showing the efficiency of the proposed approach on various instances of the paper assignment problem.