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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
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)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-68496-3_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-68495-6
Online ISBN: 978-3-319-68496-3
eBook Packages: Computer ScienceComputer Science (R0)