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Generating Experimental Data for the Generalized Assignment Problem

Author

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  • H. Edwin Romeijn

    (Department of Industrial and Systems Engineering, University of Florida, 303 Weil Hall, P.O. Box 116595, Gainesville, Florida 32611-6595)

  • Dolores Romero Morales

    (Faculty of Economics and Business Administration, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands)

Abstract

The Generalized Assignment Problem (GAP) is the problem of finding the minimal cost assignment of jobs to machines such that each job is assigned to exactly one machine, subject to capacity restrictions on the machines. We propose a new stochastic model for the GAP. A tight condition on this stochastic model under which the GAP is feasible with probability one when the number of jobs goes to infinity is derived. This new stochastic model enables us to analyze the adequacy of most of the random generators given for the GAP in the literature. We demonstrate that the random generators commonly used to test solution procedures for the GAP tend to create easier problem instances when the number of machines m increases. We describe a greedy heuristic for the GAP, and use it to illustrate the results from the paper.

Suggested Citation

  • H. Edwin Romeijn & Dolores Romero Morales, 2001. "Generating Experimental Data for the Generalized Assignment Problem," Operations Research, INFORMS, vol. 49(6), pages 866-878, December.
    • Handle: RePEc:inm:oropre:v:49:y:2001:i:6:p:866-878
    DOI: 10.1287/opre.49.6.866.10021
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    References listed on IDEAS

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    1. H. Edwin Romeijn & Dolores Romero Morales, 2003. "An asymptotically optimal greedy heuristic for the multiperiod single‐sourcing problem: The cyclic case," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(5), pages 412-437, August.
    2. Richard Freling & H. Edwin Romeijn & Dolores Romero Morales & Albert P. M. Wagelmans, 2003. "A Branch-and-Price Algorithm for the Multiperiod Single-Sourcing Problem," Operations Research, INFORMS, vol. 51(6), pages 922-939, December.

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