An effective PSO-inspired algorithm for the team orienteering problem

• Published in: European journal of operational research Vol. 229; no. 2; pp. 332 - 344
• Main Authors: Dang, Duc-Cuong, Guibadj, Rym Nesrine, Moukrim, Aziz
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.09.2013; Elsevier; Elsevier Sequoia S.A
• Subjects: Algorithms; Benchmarking; Benchmarks; Computer Science; Cost engineering; Customers; Errors; Interval graph; Knapsack problem; Mathematical models; Operations Research; Optimal split; Optimization; Optimization algorithms; Orienteering; Route optimization; Studies; Swarm intelligence; Transportation problem (Operations research); Vehicle routing; Interval graph; Swarm intelligence; Vehicle routing; Optimal split; Knapsack problem
• ISSN: 0377-2217; 1872-6860; 1872-6860
• DOI: 10.1016/j.ejor.2013.02.049

•A new fast optimal split for the team orienteering problem.•An effective particle swarm algorithm (PSOiA).•PSOiA is robust and outperforms the state-of-the-art algorithms in the literature. The Team Orienteering Problem (TOP) is a particular vehicle routing problem in which the aim is to maximize the profit gained from visiting customers without exceeding a travel cost/time limit. This paper proposes a new and fast evaluation process for TOP based on an interval graph model and a Particle Swarm Optimization inspired Algorithm (PSOiA) to solve the problem. Experiments conducted on the standard benchmark of TOP clearly show that our algorithm outperforms the existing solving methods. PSOiA reached a relative error of 0.0005% whereas the best known relative error in the literature is 0.0394%. Our algorithm detects all but one of the best known solutions. Moreover, a strict improvement was found for one instance of the benchmark and a new set of larger instances was introduced.