Tabu search

A user’s guide to tabu search. We describe the main features of tabu search, emphasizing a perspective for guiding a user to understand basic implementation principles for solving combinatorial or nonlinear problems. We also identify recent developments and extensions that have contributed to increasing the efficiency of the method. One of the useful aspects of tabu search is the ability to adapt a rudimentary prototype implementation to encompass additional model elements, such as new types of constraints and objective functions. Similarly, the method itself can be evolved to varying levels of sophistication. We provide several examples of discrete optimization problems to illustrate the strategic concerns of tabu search, and to show how they may be exploited in various contexts. Our presentation is motivated by the emergence of an extensive literature of computational results, which demonstrates that a well-tuned implementation makes it possible to obtain solutions of high quality for difficult problems, yielding outcomes in some settings that have not been matched by other known techniques.

References in zbMATH (referenced in 959 articles , 2 standard articles )

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  1. Bai, Ruibin; Woodward, John R.; Subramanian, Nachiappan; Cartlidge, John: Optimisation of transportation service network using $\kappa$-node large neighbourhood search (2018)
  2. Ben Jouida, Sihem; Krichen, Saoussen: A DSS based on optimizer tools and MTS meta-heuristic for the warehousing problem with conflicts (2018)
  3. Bürgy, Reinhard; Bülbül, Kerem: The job shop scheduling problem with convex costs (2018)
  4. Chen, Yuning; Hao, Jin-Kao: Two phased hybrid local search for the periodic capacitated arc routing problem (2018)
  5. De Bruecker, Philippe; Beliën, Jeroen; de Boeck, Liesje; de Jaeger, Simon; Demeulemeester, Erik: A model enhancement approach for optimizing the integrated shift scheduling and vehicle routing problem in waste collection (2018)
  6. Drezner, Tammy; Drezner, Zvi; Schöbel, Anita: The Weber obnoxious facility location model: a big arc small arc approach (2018)
  7. Hertz, Alain; Montagné, Romain; Gagnon, François: Online algorithms for the maximum $k$-colorable subgraph problem (2018)
  8. Martí, Rafael; Martínez-Gavara, Anna; Sánchez-Oro, Jesús; Duarte, Abraham: Tabu search for the dynamic bipartite drawing problem (2018)
  9. Nagata, Yuichi: Random partial neighborhood search for the post-enrollment course timetabling problem (2018)
  10. Noham, Reut; Tzur, Michal: Designing humanitarian supply chains by incorporating actual post-disaster decisions (2018)
  11. Sioud, A.; Gagné, C.: Enhanced migrating birds optimization algorithm for the permutation flow shop problem with sequence dependent setup times (2018)
  12. Umetani, Shunji; Arakawa, Masanao; Yagiura, Mutsunori: Relaxation heuristics for the set multicover problem with generalized upper bound constraints (2018)
  13. Battistutta, Michele; Schaerf, Andrea; Urli, Tommaso: Feature-based tuning of single-stage simulated annealing for examination timetabling (2017)
  14. Bueno, Marcos L. P.; Hommersom, Arjen; Lucas, Peter J. F.; Linard, Alexis: Asymmetric hidden Markov models (2017)
  15. Bürgy, Reinhard: A neighborhood for complex job shop scheduling problems with regular objectives (2017)
  16. Cabrera-Guerrero, Guillermo; Lagos, Carolina; Castañeda, Carolina; Johnson, Franklin; Paredes, Fernando; Cabrera, Enrique: Parameter tuning for local-search-based matheuristic methods (2017)
  17. Chen, Yujie; Cowling, Peter; Polack, Fiona; Remde, Stephen; Mourdjis, Philip: Dynamic optimisation of preventative and corrective maintenance schedules for a large scale urban drainage system (2017)
  18. Chen, Yuning; Hao, Jin-Kao: An iterated “hyperplane exploration” approach for the quadratic knapsack problem (2017)
  19. Coelho, Vitor N.; Oliveira, Thays A.; Coelho, Igor M.; Coelho, Bruno N.; Fleming, Peter J.; Guimarães, Frederico G.; Ramalhinho, Helena; Souza, Marcone J. F.; Talbi, El-Ghazali; Lust, Thibaut: Generic Pareto local search metaheuristic for optimization of targeted offers in a bi-objective direct marketing campaign (2017)
  20. Dib, Omar; Manier, Marie-Ange; Moalic, Laurent; Caminada, Alexandre: Combining VNS with genetic algorithm to solve the one-to-one routing issue in road networks (2017)

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