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GRASP with strategic oscillation for the α-neighbor p-center problem

Author

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  • Sánchez-Oro, J.
  • López-Sánchez, A.D.
  • Hernández-Díaz, A.G.
  • Duarte, A.

Abstract

This paper presents a competitive algorithm that combines the Greedy Randomized Adaptive Search Procedure including a Tabu Search instead of a traditional Local Search framework, with a Strategic Oscillation post-processing, to provide high-quality solutions for the α-neighbor p-center problem (α−pCP). This problem seeks to locate p facilities to service or cover a set of n demand points with the objective of minimizing the maximum distance between each demand point and its αth nearest facility. The algorithm is compared to the best method found in the state of the art, which is an extremely efficient exact procedure for the continuous variant of the problem. An extensive comparison shows the relevance of the proposal, being able to provide competitive results independently of the α value.

Suggested Citation

  • Sánchez-Oro, J. & López-Sánchez, A.D. & Hernández-Díaz, A.G. & Duarte, A., 2022. "GRASP with strategic oscillation for the α-neighbor p-center problem," European Journal of Operational Research, Elsevier, vol. 303(1), pages 143-158.
    • Handle: RePEc:eee:ejores:v:303:y:2022:i:1:p:143-158
    DOI: 10.1016/j.ejor.2022.02.038
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    References listed on IDEAS

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