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A Penalty Function Approach to Max 3-SAT Problems

Author

Listed:
  • Christian Kofler

    (Institute of Production and Operations Management, Karl-Franzens-University Graz)

  • Peter Greistorfer

    (Institute of Production and Operations Management, Karl-Franzens-University Graz)

  • Haibo Wang

    (Division of International Business & Technology Studies, Texas A&M International University)

  • Gary Kochenberger

    (University of Colorado Business School)

Abstract

We consider a penalty function approach for the solving of the Max 3-SAT problem. The algorithm introduced is a multi-start approach that makes use of elite-solution techniques derived from scatter search. More precisely, it is based on the so-called adaptive memory projection metaphor. The main focus of this paper is to demonstrate the usefulness of this projection idea in the context of the binary Max 3-SAT. We review the literature in that field, explain the metaheuristic proposed and present results on the basis of a DIMACS test set.

Suggested Citation

  • Christian Kofler & Peter Greistorfer & Haibo Wang & Gary Kochenberger, 2014. "A Penalty Function Approach to Max 3-SAT Problems," Working Paper Series, Social and Economic Sciences 2014-04, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    • Handle: RePEc:grz:wpsses:2014-04
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    File Function: First version, 2014
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    Cited by:

    1. Richard J. Forrester & Lucas A. Waddell, 2022. "Strengthening a linear reformulation of the 0-1 cubic knapsack problem via variable reordering," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 498-517, August.

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