Abstract
The Team Orienteering Problem (TOP) is the generalization to the case of multiple tours of the Orienteering Problem, known also as Selective Traveling Salesman Problem. A set of potential customers is available and a profit is collected from the visit to each customer. A fleet of vehicles is available to visit the customers, within a given time limit. The profit of a customer can be collected by one vehicle at most. The objective is to identify the customers which maximize the total collected profit while satisfying the given time limit for each vehicle. We propose two variants of a generalized tabu search algorithm and a variable neighborhood search algorithm for the solution of the TOP and show that each of these algorithms beats the already known heuristics. Computational experiments are made on standard instances.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Butt, S.E. and T.M. Cavalier. (1994). “A Heuristic for the Multiple Tour Maximum Collection Problem.” Computers and Operations Research 21, 101–111.
Butt, S.E., Ryan, D.M. (1999), An optimal solution procedure for the multiple tour maximum collection problem using column generation, Computers and Operations Research 26, 127–141.
Feillet, D., P. Dejax, and M. Gendreau. (2005). “Traveling Salesman Problems with Profits.” Transportation Science 39, 188#x2013;205.
Feillet, D., P. Dejax, and M. Gendreau. (2004). Traveling Salesman Problems with Profits, to appear in Transportation Science.
Gendreau, M., A. Hertz, and G. Laporte. (1994). “A Tabu Search Heuristic for the Vehicle Routing Problem.” Management Science 40, 1276–1290.
Golden, B., A. Assad, and R. Dahl. (1984). “Analysis of a Large Scale Vehicle Routing Problem with an Inventory Component.” Large Scale Systems 7, 181–190.
Golden, B., L. Levy, and R. Vohra. (1987). “The Orienteering Problem.” Naval Research Logistics 34, 307–318.
Glover F. (1986). “Future Paths for Integer Programming and Links to Artificial Intelligence.” Computers and Operations Research 5, 533–549.
Glover, F. and M. Laguna. (eds.) (1997). Tabu Search. Kluwer Academic Publishers.
Hansen, P. and N. Mladenović. (1999). “An Introduction to Variable Neighborhood Search.” In S. Voss et al. (eds.), Metaheuristics, Advances and Trends in Local Search Paradigms for Optimization. Kluwer Academic Publishers, Dordrecht, PP. 433–458.
Lin, S. (1965). “Computer Solutions of the Traveling Salesman Problem.” Bell System Technical Journal 44, 2245–2269.
Mladenović, N. and P. Hansen. (1997). “Variable Neighborhood Search.” Computers and Operations Research 24, 1097–1100.
Rochat, Y. and E. Taillard. (1995). “Probabilistic Diversification and Intensification in Local Search for Vehicle routing.” Journal of Heuristics 1, 147–167.
Tang, H. and E. Miller-Hooks. (2005). “A Tabu Search Heuristic for the Team Orienteering Problem.” Computers and Operations Research 32, 1379–1407.
Tsiligirides, T. (1984). “Heuristic Methods Applied to Orienteering.” Journal of the Operational Research Society 35, 797–809.
Toth, P. and D. Vigo. (eds.) (2002). The Vehicle Routing Problem. SIAM Monographs on Discrete Mathematics and Applications, Philadelphia.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Archetti, C., Hertz, A. & Speranza, M.G. Metaheuristics for the team orienteering problem. J Heuristics 13, 49–76 (2007). https://doi.org/10.1007/s10732-006-9004-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10732-006-9004-0