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A computational study of approximation algorithms for a minmax resource allocation problem

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  • Bogusz Przybysławski
  • Adam Kasperski

Abstract

A basic resource allocation problem with uncertain costs has been discussed. The problem is to minimize the total cost of choosing exactly p items out of n available. The uncertain item costs are specified as a discrete scenario set and the minmax criterion is used to choose a solution. This problem is known to be NP-hard, but several approximation algorithms exist. The aim of this paper is to investigate the quality of the solutions returned by these approximation algorithms. According to the results obtained, the randomized algorithms described are fast and output solutions of good quality, even if the problem size is large.

Suggested Citation

  • Bogusz Przybysławski & Adam Kasperski, 2012. "A computational study of approximation algorithms for a minmax resource allocation problem," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 22(2), pages 35-43.
  • Handle: RePEc:wut:journl:v:2:y:2012:p:35-43:id:1022
    DOI: 10.5277/ord120203
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    References listed on IDEAS

    as
    1. Adam Kasperski & Paweł Zieliński, 2009. "A randomized algorithm for the min-max selecting items problem with uncertain weights," Annals of Operations Research, Springer, vol. 172(1), pages 221-230, November.
    2. Aissi, Hassene & Bazgan, Cristina & Vanderpooten, Daniel, 2009. "Min-max and min-max regret versions of combinatorial optimization problems: A survey," European Journal of Operational Research, Elsevier, vol. 197(2), pages 427-438, September.
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