Approximating the least core value and least core of cooperative games with supermodular costs

Andreas S. Schulz, Nelson A. Uhan

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

We study the approximation of the least core value and the least core of supermodular cost cooperative games. We provide a framework for approximation based on oracles that approximately determine maximally violated constraints. This framework yields a 3-approximation algorithm for computing the least core value of supermodular cost cooperative games, and a polynomial-time algorithm for computing a cost allocation in the 2-approximate least core of these games. This approximation framework extends naturally to submodular profit cooperative games. For scheduling games, a special class of supermodular cost cooperative games, we give a fully polynomial-time approximation scheme for computing the least core value. For matroid profit games, a special class of submodular profit cooperative games, we give exact polynomial-time algorithms for computing the least core value as well as a least core cost allocation.

Original languageEnglish
Pages (from-to)163-180
Number of pages18
JournalDiscrete Optimization
Volume10
Issue number2
DOIs
StatePublished - May 2013
Externally publishedYes

Keywords

  • Cooperative games Least core Approximation algorithms Scheduling Matroids

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