Traveling salesman problem: a perspective review of recent research and new results with bio-inspired metaheuristics

dc.contributor.authorOsaba, Eneko
dc.contributor.authorYang, Xin She
dc.contributor.authorDel Ser, Javier
dc.contributor.institutionQuantum
dc.contributor.institutionIA
dc.date.accessioned2024-07-24T11:53:27Z
dc.date.available2024-07-24T11:53:27Z
dc.date.issued2020-01-01
dc.descriptionPublisher Copyright: © 2020 Elsevier Ltd. All rights reserved.
dc.description.abstractThe traveling salesman problem (TSP) is one of the most studied problems in computational intelligence and operations research. Since its first formulation, a myriad of works has been published proposing different alternatives for its solution. Additionally, a plethora of advanced formulations have also been proposed by the related practitioners, trying to enhance the applicability of the basic TSP. This chapter is firstly devoted to providing an informed overview on the TSP. For this reason, we first review the recent history of this research area, placing emphasis on milestone studies contributed in recent years. Next, we aim at making a step forward in the field proposing an experimentation hybridizing three different reputed bio-inspired computational metaheuristics (namely, particle swarm optimization, the firefly algorithm, and the bat algorithm) and the novelty search mechanism. For assessing the quality of the implemented methods, 15 different datasets taken from the well-known TSPLIB have been used. We end this chapter by sharing our envisioned status of the field, for which we identify opportunities and challenges which should stimulate research efforts in years to come.en
dc.description.statusPeer reviewed
dc.format.extent30
dc.identifier.citationOsaba , E , Yang , X S & Del Ser , J 2020 , Traveling salesman problem : a perspective review of recent research and new results with bio-inspired metaheuristics . in Nature-Inspired Computation and Swarm Intelligence : Algorithms, Theory and Applications . Elsevier , pp. 135-164 . https://doi.org/10.1016/B978-0-12-819714-1.00020-8
dc.identifier.doi10.1016/B978-0-12-819714-1.00020-8
dc.identifier.isbn9780128197141
dc.identifier.isbn9780128226094
dc.identifier.urihttps://hdl.handle.net/11556/2300
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85100132037&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofNature-Inspired Computation and Swarm Intelligence
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsbio-inspired computation
dc.subject.keywordscombinatorial optimization
dc.subject.keywordsnature-inspired computation
dc.subject.keywordsnovelty search
dc.subject.keywordsswarm intelligence
dc.subject.keywordstraveling salesman problem
dc.subject.keywordsGeneral Computer Science
dc.titleTraveling salesman problem: a perspective review of recent research and new results with bio-inspired metaheuristicsen
dc.typebook part
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