Solving the open-path asymmetric green traveling salesman problem in a realistic urban environment

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dc.contributor.authorOsaba, Eneko
dc.contributor.authorDel Ser, Javier
dc.contributor.authorIglesias, Andres
dc.contributor.authorBilbao, Miren Nekane
dc.contributor.authorFister, Iztok
dc.contributor.authorFister, Iztok
dc.contributor.authorGalvez, Akemi
dc.contributor.institutionQuantum
dc.contributor.institutionIA
dc.date.accessioned2024-07-24T11:47:48Z
dc.date.available2024-07-24T11:47:48Z
dc.date.issued2018
dc.descriptionPublisher Copyright: © 2018, Springer Nature Switzerland AG.
dc.description.abstractIn this paper, a driving route planning system for multi-point routes is designed and developed. The routing problem has modeled as an Open-Path and Asymmetric Green Traveling Salesman Problem (OAG-TSP). The main objective of the proposed OAG-TSP is to find a route between a fixed origin and destination, visiting a group of intermediate points exactly once, minimizing the CO2 emitted by the car and the total distance traveled. Thus, the developed transportation problem is a complex and multi-attribute variant of the well-known TSP. For its efficient solving, three classic meta-heuristics have been used: Simulated Annealing, Tabu Search and Variable Neighborhood Search. These approaches have been chosen for its easy adaptation and rapid execution times, something appreciated in this kind of real-world systems. The system developed has been built in a realistic simulation environment, using the open source framework Open Trip Planner. Additionally, three heterogeneous scenarios have been studied in three different cities of the Basque Country (Spain): Bilbao, Gazteiz and Donostia. Obtained results conclude that the most promising technique for solving this problem is the Simulated Annealing. The statistical significance of these findings is confirmed by the results of a Friedman’s non-parametric test.en
dc.description.sponsorshipAcknowledgements. E. Osaba and J. Del Ser would like to thank the Basque Government for its funding support through the EMAITEK program.
dc.description.statusPeer reviewed
dc.format.extent11
dc.identifier.citationOsaba , E , Del Ser , J , Iglesias , A , Bilbao , M N , Fister , I , Fister , I & Galvez , A 2018 , Solving the open-path asymmetric green traveling salesman problem in a realistic urban environment . in Studies in Computational Intelligence . Studies in Computational Intelligence , vol. 798 , Springer Verlag , pp. 181-191 . https://doi.org/10.1007/978-3-319-99626-4_16
dc.identifier.doi10.1007/978-3-319-99626-4_16
dc.identifier.issn1860-949X
dc.identifier.urihttps://hdl.handle.net/11556/1701
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85053483640&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherSpringer Verlag
dc.relation.ispartofStudies in Computational Intelligence
dc.relation.ispartofseriesStudies in Computational Intelligence
dc.relation.projectIDEusko Jaurlaritza
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsEmission reduction
dc.subject.keywordsRoute planning
dc.subject.keywordsSimulated annealing
dc.subject.keywordsTabu search
dc.subject.keywordsTraveling salesman problem
dc.subject.keywordsVariable neighborhood search
dc.subject.keywordsArtificial Intelligence
dc.subject.keywordsSDG 11 - Sustainable Cities and Communities
dc.titleSolving the open-path asymmetric green traveling salesman problem in a realistic urban environmenten
dc.typebook part
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