Comparison of two constraint programming algorithms for computing leximin-optimal allocations


We propose two constraint programming algorithms for solving the following problem: fairly and efficiently allocate a finite set of objects to a set of agents, each one having their own utilities, under admissibility constraints. Our algorithms compute an allocation maximizing the leximin order on the utility profiles of the agents. Our main contribution is the use of a cardinality meta-constraint on the one hand, and an adaptation of an existing algorithm for enforcing a multiset ordering constraint on the other hand. Moreover, we describe the application domain that motivated this work: sharing of satellite resources. We extract from this real-world application a simple and precise fair allocation problem that allows for testing and evaluating our algorithms, using a benchmark generator. The implementations of both algorithms have been tested using the constraints programming tool CHOCO [12], and a translation of the first algorithm to integer linear programming has been tested using CPLEX [10].

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@inproceedings{Bouveret2006ComparisonOT, title={Comparison of two constraint programming algorithms for computing leximin-optimal allocations}, author={Sylvain Bouveret and Michel Lemaı̂tre}, year={2006} }