Abstract
This paper addresses the Clustered Orienteering Problem, a recent variant of the Orienteering Problem. In this variant, customers are grouped into subsets called clusters. A profit is assigned to each cluster and is collected only if all customers belonging to the cluster are served. The objective is to visit the customers of a subset of clusters in order to maximize the total collected profit with respect to a travel time limit. Our solution method is based on the order first-cluster second approach. It incorporates a split procedure that converts a giant tour into an optimal solution. Experiments conducted on benchmark instances show that our algorithm outperforms the existing methods in the literature. Actually, we have found the best known solution for 916 instances from 924 with strict improvement of 82 instances.
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References
Angelelli, E., Archetti, C., Vindigni, M.: The clustered orienteering problem. European Journal of Operational Research 238(2), 404–414 (2014)
Beasley, J.E.: Route first-cluster second methods for vehicle routing. Omega 11(4), 403–408 (1983)
Bouly, H., Dang, D.-C., Moukrim, A.: A memetic algorithm for the team orienteering problem. 4OR 8(1) 49–70 (2010)
Fischetti, M., Gonzalez, J.J.S., Toth, P.: Solving the orienteering problem through branch-and-cut. INFORMS Journal on Computing 10(2), 133–148 (1998)
Lin, S., Kernighan, B.: An effective heuristic algorithm for the traveling-salesman problem. Operations Research 21(2), 498–516 (1973)
Pisinger, D., Ropke, S.: Large neighborhood search. In: Handbook of Metaheuristics, pp. 399–419. Springer (2010)
Prins, C.: A simple and effective evolutionary algorithm for the vehicle routing problem. Computers & Operations Research 31(12), 1985–2002 (2004)
Prins, C., Lacomme, P., Prodhon, C.: Order-first split-second methods for vehicle routing problems: A review. Transportation Research Part C: Emerging Technologies 40, 179–200 (2014)
Vargas, L., Jozefowiez, N., Ngueveu, S.U.: A dynamic programming operator for tour location problems applied to the covering tour problem. Journal of Heuristics 23(1), 53–80 (2017)
Vidal, T., Maculan, N., Ochi, L.S., Vaz Penna, P.H.: Large neighborhoods with implicit customer selection for vehicle routing problems with profits. Transportation Science 50(2), 720–734 (2015)
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Yahiaoui, AE., Moukrim, A., Serairi, M. (2017). Hybrid Heuristic for the Clustered Orienteering Problem. In: Bektaş, T., Coniglio, S., Martinez-Sykora, A., Voß, S. (eds) Computational Logistics. ICCL 2017. Lecture Notes in Computer Science(), vol 10572. Springer, Cham. https://doi.org/10.1007/978-3-319-68496-3_2
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DOI: https://doi.org/10.1007/978-3-319-68496-3_2
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