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Two-phase method and Lagrangian relaxation to solve the Bi-Objective Set Covering Problem

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  • Christian Prins
  • Caroline Prodhon
  • Roberto Calvo

Abstract

This paper deals with the Bi-Objective Set Covering Problem, which is a generalization of the well-known Set Covering Problem. The proposed approach is a two-phase heuristic method which has the particularity to be a constructive method using the primal-dual Lagrangian relaxation to solve single objective Set Covering problems. The results show that this algorithm finds several potentially supported and unsupported solutions. A comparison with an exact method (up to a medium size), shows that many Pareto-optimal solutions are retrieved and that the other solutions are well spread and close to the optimal ones. Moreover, the method developed compares favorably with the Pareto Memetic Algorithm proposed by Jaszkiewicz. Copyright Springer Science + Business Media, LLC 2006

Suggested Citation

  • Christian Prins & Caroline Prodhon & Roberto Calvo, 2006. "Two-phase method and Lagrangian relaxation to solve the Bi-Objective Set Covering Problem," Annals of Operations Research, Springer, vol. 147(1), pages 23-41, October.
  • Handle: RePEc:spr:annopr:v:147:y:2006:i:1:p:23-41:10.1007/s10479-006-0060-5
    DOI: 10.1007/s10479-006-0060-5
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    References listed on IDEAS

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    1. Mark S. Daskin & Edmund H. Stern, 1981. "A Hierarchical Objective Set Covering Model for Emergency Medical Service Vehicle Deployment," Transportation Science, INFORMS, vol. 15(2), pages 137-152, May.
    2. Beasley, J. E., 1987. "An algorithm for set covering problem," European Journal of Operational Research, Elsevier, vol. 31(1), pages 85-93, July.
    3. Alberto Caprara & Matteo Fischetti & Paolo Toth, 1999. "A Heuristic Method for the Set Covering Problem," Operations Research, INFORMS, vol. 47(5), pages 730-743, October.
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    Cited by:

    1. Rafael Lazimy, 2013. "Interactive Polyhedral Outer Approximation (IPOA) strategy for general multiobjective optimization problems," Annals of Operations Research, Springer, vol. 210(1), pages 73-99, November.
    2. Lakmali Weerasena & Aniekan Ebiefung & Anthony Skjellum, 2022. "Design of a heuristic algorithm for the generalized multi-objective set covering problem," Computational Optimization and Applications, Springer, vol. 82(3), pages 717-751, July.
    3. Florios, Kostas & Mavrotas, George, 2014. "Generation of the exact Pareto set in multi-objective traveling salesman and set covering problems," MPRA Paper 105074, University Library of Munich, Germany.
    4. Lakmali Weerasena & Margaret M. Wiecek & Banu Soylu, 2017. "An algorithm for approximating the Pareto set of the multiobjective set covering problem," Annals of Operations Research, Springer, vol. 248(1), pages 493-514, January.
    5. N Safaei & D Banjevic & A K S Jardine, 2011. "Bi-objective workforce-constrained maintenance scheduling: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1005-1018, June.

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