Document Type

Article

Publication Date

5-2017

Subject: LCSH

Constraint programming (Computer science), Vehicle routing problem

Disciplines

Industrial Engineering | Mechanical Engineering

Abstract

The team orienteering problem with time windows (TOPTW) is a NP-hard combinatorial optimization problem. It has many real-world applications, for example, routing technicians and disaster relief routing. In the TOPTW, a set of locations is given. For each, the profit, service time and time window are known. A fleet of homogenous vehicles are available for visiting locations and collecting their associated profits. Each vehicle is constrained by a maximum tour duration. The problem is to plan a set of vehicle routes that begin and end at a depot, visit each location no more than once by incorporating time window constraints. The objective is to maximize the profit collected. In this study we discuss how to use constraint programming (CP) to formulate and solve TOPTW by applying interval variables, global constraints and domain filtering algorithms. We propose a CP model and two branching strategies for the TOPTW. The approach finds 119 of the best-known solutions for 304 TOPTW benchmark instances from the literature. Moreover, the proposed method finds one new best-known solution for TOPTW benchmark instances and proves the optimality of the best-known solutions for two additional instances.

Comments

This is the authors' accepted manuscript of the article published in Computers & Industrial Engineering. The version of record is posted at http://dx.doi.org/10.1016/j.cie.2017.03.017

DOI

10.1016/j.cie.2017.03.017

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Publisher Citation

Gedik, R., Kirac, E., Milburn, A. B., & Rainwater, C. (2017). A constraint programming approach for the team orienteering problem with time windows. Computers & Industrial Engineering, 107, 178-195.

Available for download on Tuesday, March 17, 2020

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