A Discrete and Improved Bat Algorithm for solving a medical goods distribution problem with pharmacological waste collection

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dc.contributor.authorOsaba, Eneko
dc.contributor.authorYang, Xin-She
dc.contributor.authorFister, Iztok
dc.contributor.authorDel Ser, Javier
dc.contributor.authorLopez-Garcia, Pedro
dc.contributor.authorVazquez-Pardavila, Alejo J.
dc.contributor.institutionTecnalia Research & Innovation
dc.contributor.institutionQuantum
dc.contributor.institutionIA
dc.date.issued2019-02
dc.descriptionPublisher Copyright: © 2018 Elsevier B.V.
dc.description.abstractThe work presented in this paper is focused on the resolution of a real-world drugs distribution problem with pharmacological waste collection. With the aim of properly meeting all the real-world restrictions that comprise this complex problem, we have modeled it as a multi-attribute or rich vehicle routing problem (RVRP). The problem has been modeled as a Clustered Vehicle Routing Problem with Pickups and Deliveries, Asymmetric Variable Costs, Forbidden Roads and Cost Constraints. To the best of authors knowledge, this is the first time that such a RVRP problem is tackled in the literature. For this reason, a benchmark composed of 24 datasets, from 60 to 1000 customers, has also been designed. For the developing of this benchmark, we have used real geographical positions located in Bizkaia, Spain. Furthermore, for the proper dealing of the proposed RVRP, we have developed a Discrete and Improved Bat Algorithm (DaIBA). The main feature of this adaptation is the use of the well-known Hamming Distance to calculate the differences between the bats. An effective improvement has been also contemplated for the proposed DaIBA, which consists on the existence of two different neighborhood structures, which are explored depending on the bat's distance regarding the best individual of the swarm. For the experimentation, we have compared the performance of our presented DaIBA with three additional approaches: an evolutionary algorithm, an evolutionary simulated annealing and a firefly algorithm. Additionally, with the intention of obtaining rigorous conclusions, two different statistical tests have been conducted: the Friedman's non-parametric test and the Holm's post-hoc test. Furthermore, an additional experimentation has been performed in terms of convergence. Finally, the obtained outcomes conclude that the proposed DaIBA is a promising technique for addressing the designed problem.en
dc.description.statusPeer reviewed
dc.format.extent14
dc.format.extent285185
dc.identifier.citationOsaba , E , Yang , X-S , Fister , I , Del Ser , J , Lopez-Garcia , P & Vazquez-Pardavila , A J 2019 , ' A Discrete and Improved Bat Algorithm for solving a medical goods distribution problem with pharmacological waste collection ' , Swarm and Evolutionary Computation , vol. 44 , pp. 273-286 . https://doi.org/10.1016/j.swevo.2018.04.001
dc.identifier.doi10.1016/j.swevo.2018.04.001
dc.identifier.issn2210-6502
dc.identifier.otherresearchoutputwizard: 11556/556
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85045180765&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofSwarm and Evolutionary Computation
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsBat algorithm
dc.subject.keywordsMedical distribution
dc.subject.keywordsRich vehicle routing problem
dc.subject.keywordsCombinatorial optimization
dc.subject.keywordsTraveling Salesman Problem
dc.subject.keywordsBat algorithm
dc.subject.keywordsMedical distribution
dc.subject.keywordsRich vehicle routing problem
dc.subject.keywordsCombinatorial optimization
dc.subject.keywordsTraveling Salesman Problem
dc.subject.keywordsGeneral Computer Science
dc.subject.keywordsGeneral Mathematics
dc.subject.keywordsSDG 11 - Sustainable Cities and Communities
dc.titleA Discrete and Improved Bat Algorithm for solving a medical goods distribution problem with pharmacological waste collectionen
dc.typejournal article
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