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Variable neighbourhood search: methods and applications

Author

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  • Pierre Hansen

    ()

  • Nenad Mladenović

    ()

  • José Moreno Pérez

    ()

Abstract

Variable neighbourhood search (VNS) is a metaheuristic, or a framework for building heuristics, based upon systematic changes of neighbourhoods both in descent phase, to find a local minimum, and in perturbation phase to emerge from the corresponding valley. It was first proposed in 1997 and has since then rapidly developed both in its methods and its applications. In the present paper, these two aspects are thoroughly reviewed and an extensive bibliography is provided. Moreover, one section is devoted to newcomers. It consists of steps for developing a heuristic for any particular problem. Those steps are common to the implementation of other metaheuristics. Copyright Springer Science+Business Media, LLC 2010

Suggested Citation

  • Pierre Hansen & Nenad Mladenović & José Moreno Pérez, 2010. "Variable neighbourhood search: methods and applications," Annals of Operations Research, Springer, vol. 175(1), pages 367-407, March.
  • Handle: RePEc:spr:annopr:v:175:y:2010:i:1:p:367-407:10.1007/s10479-009-0657-6
    DOI: 10.1007/s10479-009-0657-6
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    Citations

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    Cited by:

    1. Prieto Fernández, Francisco Javier & Martín Barragán, Belén & Liu, Ling, 2016. "A Partial parametric path algorithm for multiclass classification," DES - Working Papers. Statistics and Econometrics. WS 22390, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Chandra Ade Irawan & Said Salhi & Zvi Drezner, 2016. "Hybrid meta-heuristics with VNS and exact methods: application to large unconditional and conditional vertex $$p$$ p -centre problems," Journal of Heuristics, Springer, vol. 22(4), pages 507-537, August.
    3. Elshaikh, Abdalla & Salhi, Said & Nagy, Gábor, 2015. "The continuous p-centre problem: An investigation into variable neighbourhood search with memory," European Journal of Operational Research, Elsevier, vol. 241(3), pages 606-621.
    4. Chen, Yujie & Cowling, Peter & Polack, Fiona & Remde, Stephen & Mourdjis, Philip, 2017. "Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system," European Journal of Operational Research, Elsevier, vol. 257(2), pages 494-510.
    5. repec:eee:ejores:v:264:y:2018:i:1:p:55-65 is not listed on IDEAS
    6. López, C.O. & Beasley, J.E., 2011. "A heuristic for the circle packing problem with a variety of containers," European Journal of Operational Research, Elsevier, vol. 214(3), pages 512-525, November.
    7. repec:spr:annopr:v:259:y:2017:i:1:d:10.1007_s10479-017-2508-1 is not listed on IDEAS
    8. repec:spr:annopr:v:258:y:2017:i:2:d:10.1007_s10479-016-2261-x is not listed on IDEAS
    9. Todosijević, Raca & Benmansour, Rachid & Hanafi, Saïd & Mladenović, Nenad & Artiba, Abdelhakim, 2016. "Nested general variable neighborhood search for the periodic maintenance problem," European Journal of Operational Research, Elsevier, vol. 252(2), pages 385-396.
    10. 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.
    11. Zhang, Ying & Snyder, Lawrence V. & Ralphs, Ted K. & Xue, Zhaojie, 2016. "The competitive facility location problem under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 453-473.
    12. repec:eee:ejores:v:263:y:2017:i:2:p:419-445 is not listed on IDEAS
    13. repec:spr:eurjco:v:5:y:2017:i:3:d:10.1007_s13675-016-0075-x is not listed on IDEAS
    14. Santi, Éverton & Aloise, Daniel & Blanchard, Simon J., 2016. "A model for clustering data from heterogeneous dissimilarities," European Journal of Operational Research, Elsevier, vol. 253(3), pages 659-672.
    15. repec:eee:ejores:v:261:y:2017:i:3:p:819-834 is not listed on IDEAS
    16. Hof, Julian & Schneider, Michael & Goeke, Dominik, 2017. "Solving the battery swap station location-routing problem with capacitated electric vehicles using an AVNS algorithm for vehicle-routing problems with intermediate stops," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 102-112.
    17. repec:eee:transb:v:106:y:2017:i:c:p:237-265 is not listed on IDEAS
    18. Benati, Stefano & Puerto, Justo & Rodríguez-Chía, Antonio M., 2017. "Clustering data that are graph connected," European Journal of Operational Research, Elsevier, vol. 261(1), pages 43-53.
    19. Gahm, Christian & Brabänder, Christian & Tuma, Axel, 2017. "Vehicle routing with private fleet, multiple common carriers offering volume discounts, and rental options," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 192-216.
    20. repec:spr:joheur:v:23:y:2017:i:2:d:10.1007_s10732-017-9331-3 is not listed on IDEAS
    21. Irawan, Chandra Ade & Song, Xiang & Jones, Dylan & Akbari, Negar, 2017. "Layout optimisation for an installation port of an offshore wind farm," European Journal of Operational Research, Elsevier, vol. 259(1), pages 67-83.
    22. Pierre Hansen & Nenad Mladenović & Raca Todosijević & Saïd Hanafi, 0. "Variable neighborhood search: basics and variants," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 0, pages 1-32.
    23. repec:spr:joheur:v:24:y:2018:i:1:d:10.1007_s10732-017-9357-6 is not listed on IDEAS
    24. repec:eee:transe:v:109:y:2018:i:c:p:1-19 is not listed on IDEAS

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