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Hybrid heuristics for minimum cardinality set covering problems

Author

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  • Francis J. Vasko
  • George R. Wilson

Abstract

Minimum cardinality set covering problems (MCSCP) tend to be more difficult to solve than weighted set covering problems because the cost or weight associated with each variable is the same. Since MCSCP is NP‐complete, large problem instances are commonly solved using some form of a greedy heuristic. In this paper hybrid algorithms are developed and tested against two common forms of the greedy heuristic. Although all the algorithms tested have the same worst case bounds provided by Ho [7], empirical results for 60 large randomly generated problems indicate that one algorithm performed better than the others.

Suggested Citation

  • Francis J. Vasko & George R. Wilson, 1986. "Hybrid heuristics for minimum cardinality set covering problems," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 33(2), pages 241-249, May.
    • Handle: RePEc:wly:navlog:v:33:y:1986:i:2:p:241-249
    DOI: 10.1002/nav.3800330207
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    Cited by:

    1. Ye, Lin & Ye, Chunming & Chuang, Yi-Fei, 2011. "Location set covering for waste resource recycling centers in Taiwan," Resources, Conservation & Recycling, Elsevier, vol. 55(11), pages 979-985.
    2. J. E. Beasley, 1990. "A lagrangian heuristic for set‐covering problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 37(1), pages 151-164, February.
    3. Marc Almiñana & Jesús Pastor, 1997. "A comparison of algorithm RS with algorithm OPTSOL70," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(2), pages 213-219, December.
    4. Brian J. Lunday & J. Cole Smith & Jeffrey B. Goldberg, 2005. "Algorithms for solving the conditional covering problem on paths," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(4), pages 293-301, June.

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