An iterated local search algorithm for the team orienteering problem with variable profits

Gunawan, Aldy, Ng, Kien Ming, Kendall, Graham and Lai, Junhan (2018) An iterated local search algorithm for the team orienteering problem with variable profits. Engineering Optimization . ISSN 1029-0273

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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.

Item Type: Article
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in Engineering Optimization on 16 January 2018, available online:
Keywords: Orienteering problem, variable profit, mathematical programming model, iterated local search
Schools/Departments: University of Nottingham, Malaysia > Faculty of Science and Engineering — Science > School of Computer Science
University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number:
Depositing User: Kendall, Graham
Date Deposited: 06 Feb 2018 14:23
Last Modified: 04 May 2020 19:27

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