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An algorithm portfolio for the dynamic maximal covering location problem

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Abstract

The location of facilities (antennas, ambulances, police patrols, etc) has been widely studied in the literature. The maximal covering location problem aims at locating the facilities in such positions that maximizes certain notion of coverage. In the dynamic or multi-period version of the problem, it is assumed that the nodes’ demand changes with the time and as a consequence, facilities can be opened or closed among the periods. In this contribution we propose to solve dynamic maximal covering location problem using an algorithm portfolio that includes adaptation, cooperation and learning. The portfolio is composed of an evolutionary strategy and three different simulated annealing methods (that were recently used to solve the problem). Experiments were conducted on 45 test instances (considering up to 2500 nodes and 200 potential facility locations). The results clearly show that the performance of the portfolio is significantly better than its constituent algorithms.

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Notes

  1. CEC stands for Conference on Evolutionary Computation, where competitions over well-defined optimization problems’ benchmarks are done.

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Acknowledgments

Jenny Fajardo Calderín has been supported by a scholarship from the Eureka SD from Erasmus Mundus Action 2 Project coordinated by the University of Oldenburg. David A. Pelta is supported by projects TIN2014-55024-P (Spanish Ministry of Economy and Competitiveness) and P11-TIC-8001 ( Consejería de Economía, Innovación y Ciencia, Junta de Andalucía). Both projects include FEDER funds from the European Union). Antonio D. Masegosa is supported by the research projects TEC2013-45585-C2-2-R and TIN2014-56042-JIN from the Spanish Ministry of Economy and Competitiveness.

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Authors and Affiliations

  1. Department of Articial Intelligence and Infrastructure and Systems, Polytechnic Higher Institute José A. Echeverría, Havana, Cuba

    Jenny Fajardo Calderín

  2. Faculty of Engineering, University of Deusto, 48007, Bilbao, Spain

    Antonio D. Masegosa

  3. DeustoTech-Fundacion Deusto, Deusto Foundation, 48007, Bilbao, Spain

    Antonio D. Masegosa

  4. IKERBASQUE, Basque Foundation for Science, 48011, Bilbao, Spain

    Antonio D. Masegosa

  5. Department of Computer Science and AI, University of Granada, Granada, Spain

    David A. Pelta

Authors
  1. Jenny Fajardo Calderín
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  2. Antonio D. Masegosa
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  3. David A. Pelta
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Correspondence to Jenny Fajardo Calderín.

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Calderín, J.F., Masegosa, A.D. & Pelta, D.A. An algorithm portfolio for the dynamic maximal covering location problem. Memetic Comp. 9, 141–151 (2017). https://doi.org/10.1007/s12293-016-0210-5

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  • DOI: https://doi.org/10.1007/s12293-016-0210-5

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