Publication Type

Journal Article

Version

acceptedVersion

Publication Date

1-2018

Abstract

The orienteering problem (OP) is a routing problem that has numerous applications in various domains such as logistics and tourism. The objective is to determine a subset of vertices to visit for a vehicle so that the total collected score is maximized and a given time budget is not exceeded. The extensive application of the OP has led to many different variants, including the team orienteering problem (TOP) and the team orienteering problem with time windows. The TOP extends the OP by considering multiple vehicles. In this article, the team orienteering problem with variable profits (TOPVP) is studied. The main characteristic of the TOPVP is that the amount of score collected from a visited vertex depends on the duration of stay on that vertex. A mathematical programming model for the TOPVP is first presented and an algorithm based on iterated local search (ILS) that is able to solve modified benchmark instances is then proposed. It is concluded that ILS produces solutions which are comparable to those obtained by the commercial solver CPLEX for smaller instances. For the larger instances, ILS obtains good-quality solutions that have significantly better objective value than those found by CPLEX under reasonable computational times.

Keywords

Orienteering problem, variable profit, mathematical programming model, iterated local search

Discipline

Software Engineering | Theory and Algorithms

Research Areas

Intelligent Systems and Optimization

Publication

Engineering Optimization

Volume

50

First Page

1148

Last Page

1163

ISSN

0305-215X

Identifier

10.1080/0305215X.2017.1417398

Publisher

Taylor & Francis

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1080/0305215X.2017.1417398

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