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Greedy Randomized Adaptive Search Procedures: Advances, Hybridizations, and Applications

In: Handbook of Metaheuristics

Author

Listed:
  • Mauricio G.C. Resende

    (AT&T Labs Research)

  • Celso C. Ribeiro

    (Universidade Federal Fluminense)

Abstract
GRASP is a multi-start metaheuristic for combinatorial optimization problems, in which each iteration consists basically of two phases: construction and local search. The construction phase builds a feasible solution, whose neighborhood is investigated until a local minimum is found during the local search phase. The best overall solution is kept as the result. In this chapter, we first describe the basic components of GRASP. Successful implementation techniques are discussed and illustrated by numerical results obtained for different applications. Enhanced or alternative solution construction mechanisms and techniques to speed up the search are also described: alternative randomized greedy construction schemes, Reactive GRASP, cost perturbations, bias functions, memory and learning, local search on partially constructed solutions, hashing, and filtering. We also discuss implementation strategies of memory-based intensification and post-optimization techniques using path-relinking. Hybridizations with other metaheuristics, parallelization strategies, and applications are also reviewed.

Suggested Citation

  • Mauricio G.C. Resende & Celso C. Ribeiro, 2010. "Greedy Randomized Adaptive Search Procedures: Advances, Hybridizations, and Applications," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 283-319, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-1665-5_10
    DOI: 10.1007/978-1-4419-1665-5_10
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    Citations

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    Cited by:

    1. Maria Albareda-Sambola & Elena Fernández & Francisco Saldanha-da-Gama, 2017. "Heuristic Solutions to the Facility Location Problem with General Bernoulli Demands," INFORMS Journal on Computing, INFORMS, vol. 29(4), pages 737-753, November.
    2. Fernando Stefanello & Vaneet Aggarwal & Luciana S. Buriol & Mauricio G. C. Resende, 2019. "Hybrid algorithms for placement of virtual machines across geo-separated data centers," Journal of Combinatorial Optimization, Springer, vol. 38(3), pages 748-793, October.
    3. Angel Juan & Javier Faulin & Albert Ferrer & Helena Lourenço & Barry Barrios, 2013. "MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 109-132, April.
    4. Duarte, Abraham & Martí, Rafael & Álvarez, Ada & Ángel-Bello, Francisco, 2012. "Metaheuristics for the linear ordering problem with cumulative costs," European Journal of Operational Research, Elsevier, vol. 216(2), pages 270-277.
    5. Musmanno, Leonardo M. & Ribeiro, Celso C., 2016. "Heuristics for the generalized median graph problem," European Journal of Operational Research, Elsevier, vol. 254(2), pages 371-384.
    6. Shuli Hu & Xiaoli Wu & Huan Liu & Yiyuan Wang & Ruizhi Li & Minghao Yin, 2019. "Multi-Objective Neighborhood Search Algorithm Based on Decomposition for Multi-Objective Minimum Weighted Vertex Cover Problem," Sustainability, MDPI, vol. 11(13), pages 1-21, July.
    7. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2020. "Cost minimization of large-scale infrastructure for electricity generation and transmission," Omega, Elsevier, vol. 96(C).
    8. Yupeng Zhou & Jinshu Li & Yang Liu & Shuai Lv & Yong Lai & Jianan Wang, 2020. "Improved Memetic Algorithm for Solving the Minimum Weight Vertex Independent Dominating Set," Mathematics, MDPI, vol. 8(7), pages 1-17, July.
    9. Coelho, V.N. & Grasas, A. & Ramalhinho, H. & Coelho, I.M. & Souza, M.J.F. & Cruz, R.C., 2016. "An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints," European Journal of Operational Research, Elsevier, vol. 250(2), pages 367-376.
    10. Villegas, Juan G. & Prins, Christian & Prodhon, Caroline & Medaglia, Andrés L. & Velasco, Nubia, 2013. "A matheuristic for the truck and trailer routing problem," European Journal of Operational Research, Elsevier, vol. 230(2), pages 231-244.
    11. Victor Reyes & Ignacio Araya, 2021. "A GRASP-based scheme for the set covering problem," Operational Research, Springer, vol. 21(4), pages 2391-2408, December.
    12. Coelho, Vitor N. & Coelho, Igor M. & Coelho, Bruno N. & Reis, Agnaldo J.R. & Enayatifar, Rasul & Souza, Marcone J.F. & Guimarães, Frederico G., 2016. "A self-adaptive evolutionary fuzzy model for load forecasting problems on smart grid environment," Applied Energy, Elsevier, vol. 169(C), pages 567-584.
    13. Kamilla Hamre Bolstad & Manu Joshi & Lars Magnus Hvattum & Magnus Stålhane, 2022. "Composing Vessel Fleets for Maintenance at Offshore Wind Farms by Solving a Dual-Level Stochastic Programming Problem Using GRASP," Logistics, MDPI, vol. 6(1), pages 1-22, January.
    14. Bulhões, Teobaldo & Subramanian, Anand & Erdoğan, Güneş & Laporte, Gilbert, 2018. "The static bike relocation problem with multiple vehicles and visits," European Journal of Operational Research, Elsevier, vol. 264(2), pages 508-523.
    15. Sohrabi, Somayeh & Ziarati, Koorush & Keshtkaran, Morteza, 2020. "A Greedy Randomized Adaptive Search Procedure for the Orienteering Problem with Hotel Selection," European Journal of Operational Research, Elsevier, vol. 283(2), pages 426-440.
    16. Skorin-Kapov, Nina & Furdek, Marija & Aparicio Pardo, Ramon & Mariño, Pablo Pavón, 2012. "Wavelength assignment for reducing in-band crosstalk attack propagation in optical networks: ILP formulations and heuristic algorithms," European Journal of Operational Research, Elsevier, vol. 222(3), pages 418-429.
    17. Simona Mancini, 2013. "Multi-echelon distribution systems in city logistics," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 54, pages 1-2.
    18. Martí, Rafael & Resende, Mauricio G.C. & Ribeiro, Celso C., 2013. "Multi-start methods for combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 226(1), pages 1-8.

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