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Iterated Local Search: Framework and Applications

In: Handbook of Metaheuristics

Author

Listed:
  • Helena Ramalhinho Lourenço

    (Universitat Pompeu Fabra)

  • Olivier C. Martin

    (Université Paris-Sud)

  • Thomas Stützle

    (Université Libre de Bruxelles (ULB))

Abstract

The key idea underlying iterated local search is to focus the search not on the full space of all candidate solutions but on the solutions that are returned by some underlying algorithm, typically a local search heuristic. The resulting search behavior can be characterized as iteratively building a chain of solutions of this embedded algorithm. The result is also a conceptually simple metaheuristic that nevertheless has led to state-of-the-art algorithms for many computationally hard problems. In fact, very good performance is often already obtained by rather straightforward implementations of the metaheuristic. In addition, the modular architecture of iterated local search makes it very suitable for an algorithm engineering approach where, progressively, the algorithm’s performance can be further optimized. Our purpose here is to give an accessible description of the underlying principles of iterated local search and a discussion of the main aspects that need to be taken into account for a successful application of it. In addition, we review the most important applications of this method and discuss its relationship with other metaheuristics.

Suggested Citation

  • Helena Ramalhinho Lourenço & Olivier C. Martin & Thomas Stützle, 2019. "Iterated Local Search: Framework and Applications," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, edition 3, chapter 0, pages 129-168, Springer.
  • Handle: RePEc:spr:isochp:978-3-319-91086-4_5
    DOI: 10.1007/978-3-319-91086-4_5
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    Citations

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    Cited by:

    1. Paredes-Belmar, Germán & Montero, Elizabeth & Lüer-Villagra, Armin & Marianov, Vladimir & Araya-Sassi, Claudio, 2022. "Vehicle routing for milk collection with gradual blending: A case arising in Chile," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1403-1416.
    2. Calmels, Dorothea, 2022. "An iterated local search procedure for the job sequencing and tool switching problem with non-identical parallel machines," European Journal of Operational Research, Elsevier, vol. 297(1), pages 66-85.
    3. Gandra, Vinícius S.M. & Çalık, Hatice & Toffolo, Túlio A.M. & Carvalho, Marco Antonio M. & Vanden Berghe, Greet, 2022. "The vessel swap-body routing problem," European Journal of Operational Research, Elsevier, vol. 303(1), pages 354-369.
    4. Albert Einstein Fernandes Muritiba & Tibérius O. Bonates & Stênio Oliveira Da Silva & Manuel Iori, 2021. "Branch-and-Cut and Iterated Local Search for the Weighted k -Traveling Repairman Problem: An Application to the Maintenance of Speed Cameras," Transportation Science, INFORMS, vol. 55(1), pages 139-159, 1-2.
    5. Fowler, John W. & Mönch, Lars, 2022. "A survey of scheduling with parallel batch (p-batch) processing," European Journal of Operational Research, Elsevier, vol. 298(1), pages 1-24.
    6. Yinghui Wu & Haoran Du & Huixin Song, 2024. "An Iterated Local Search Heuristic for the Multi-Trip Vehicle Routing Problem with Multiple Time Windows," Mathematics, MDPI, vol. 12(11), pages 1-16, May.
    7. Zandieh, Fatemeh & Ghannadpour, Seyed Farid & Mazdeh, Mohammad Mahdavi, 2024. "New integrated routing and surveillance model with drones and charging station considerations," European Journal of Operational Research, Elsevier, vol. 313(2), pages 527-547.
    8. Eduardo Queiroga & Rian G. S. Pinheiro & Quentin Christ & Anand Subramanian & Artur A. Pessoa, 2021. "Iterated local search for single machine total weighted tardiness batch scheduling," Journal of Heuristics, Springer, vol. 27(3), pages 353-438, June.
    9. Máximo, Vinícius R. & Nascimento, Mariá C.V., 2021. "A hybrid adaptive iterated local search with diversification control to the capacitated vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1108-1119.
    10. Alvarez, Aldair & Miranda, Pedro & Rohmer, S.U.K., 2022. "Production routing for perishable products," Omega, Elsevier, vol. 111(C).
    11. Wu, Song & Yang, Wei & Hanafi, Saïd & Wilbaut, Christophe & Wang, Yang, 2024. "Iterated local search with ejection chains for the space-free multi-row facility layout problem," European Journal of Operational Research, Elsevier, vol. 316(3), pages 873-886.
    12. Chen-Kun Tsung & Tseng-Fung Ho & Hsuan-Yu Huang & Shu-Hui Yang & Po-Nien Tsou & Ming-Cheng Tsai & Yi-Ping Huang, 2020. "Computing the Assembly Guidance for Maximizing Product Quality in the Virtual Assembly," Sustainability, MDPI, vol. 12(11), pages 1-14, June.
    13. Bernardino, Raquel & Paias, Ana, 2024. "The family capacitated vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 314(3), pages 836-853.

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