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A fast swap-based local search procedure for location problems

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  • Mauricio Resende
  • Renato Werneck

Abstract

We present a new implementation of a widely used swap-based local search procedure for the p-median problem, proposed in 1968 by Teitz and Bart. Our method produces the same output as the best alternatives described in the literature and, even though its worst-case complexity is similar, it can be significantly faster in practice: speedups of up to three orders of magnitude were observed. We also show that our method can be easily adapted to handle the facility location problem and to implement related procedures, such as path-relinking and tabu search. Copyright Springer Science+Business Media, LLC 2007

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  • Mauricio Resende & Renato Werneck, 2007. "A fast swap-based local search procedure for location problems," Annals of Operations Research, Springer, vol. 150(1), pages 205-230, March.
    • Handle: RePEc:spr:annopr:v:150:y:2007:i:1:p:205-230:10.1007/s10479-006-0154-0
    DOI: 10.1007/s10479-006-0154-0
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    References listed on IDEAS

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    Cited by:

    1. Wangshu Mu & Daoqin Tong, 2020. "On solving large p-median problems," Environment and Planning B, , vol. 47(6), pages 981-996, July.
    2. Yılmaz, Seren Bilge & Yücel, Eda, 2021. "Optimizing onboard catering loading locations and plans for airlines," Omega, Elsevier, vol. 99(C).
    3. Abdolsalam Ghaderi & Mohammad Jabalameli & Farnaz Barzinpour & Ragheb Rahmaniani, 2012. "An Efficient Hybrid Particle Swarm Optimization Algorithm for Solving the Uncapacitated Continuous Location-Allocation Problem," Networks and Spatial Economics, Springer, vol. 12(3), pages 421-439, September.
    4. Irawan, Chandra Ade & Salhi, Said & Scaparra, Maria Paola, 2014. "An adaptive multiphase approach for large unconditional and conditional p-median problems," European Journal of Operational Research, Elsevier, vol. 237(2), pages 590-605.
    5. Sáez-Aguado, Jesús & Trandafir, Paula Camelia, 2012. "Some heuristic methods for solving p-median problems with a coverage constraint," European Journal of Operational Research, Elsevier, vol. 220(2), pages 320-327.
    6. Sayarshad, Hamid R. & Chow, Joseph Y.J., 2017. "Non-myopic relocation of idle mobility-on-demand vehicles as a dynamic location-allocation-queueing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 60-77.
    7. Dong-Guen Kim & Yeong-Dae Kim, 2013. "A Lagrangian heuristic algorithm for a public healthcare facility location problem," Annals of Operations Research, Springer, vol. 206(1), pages 221-240, July.
    8. Shilian Han & Jerry Mendel, 2012. "A new method for managing the uncertainties in evaluating multi-person multi-criteria location choices, using a perceptual computer," Annals of Operations Research, Springer, vol. 195(1), pages 277-309, May.
    9. B. Jayalakshmi & Alok Singh, 2017. "A hybrid artificial bee colony algorithm for the p-median problem with positive/negative weights," OPSEARCH, Springer;Operational Research Society of India, vol. 54(1), pages 67-93, March.
    10. Amaldi, Edoardo & Coniglio, Stefano, 2013. "A distance-based point-reassignment heuristic for the k-hyperplane clustering problem," European Journal of Operational Research, Elsevier, vol. 227(1), pages 22-29.
    11. Kim, Dong-Guen & Kim, Yeong-Dae, 2010. "A branch and bound algorithm for determining locations of long-term care facilities," European Journal of Operational Research, Elsevier, vol. 206(1), pages 168-177, October.
    12. Francisco Casas & Claudio E. Torres & Ignacio Araya, 2022. "A heuristic search based on diversity for solving combinatorial problems," Journal of Heuristics, Springer, vol. 28(3), pages 287-328, June.

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