<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/6017B6C5-4B7D-42BE-8321-C9D19E8A25CB"><efrbr-work:titleOfTheWork>A hybrid particle swarm optimization – variable neighborhood search algorithm for constrained shortest path problems</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/6017B6C5-4B7D-42BE-8321-C9D19E8A25CB"><efrbr-expression:titleOfTheExpression>A hybrid particle swarm optimization – variable neighborhood search algorithm for constrained shortest path problems</efrbr-expression:titleOfTheExpression><efrbr-expression:formOfExpression vocabulary="DIAS:TYPES">
            Peer-Reviewed Journal Publication
            Δημοσίευση σε Περιοδικό με Κριτές
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2018-03-26</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">2017</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent>In this paper, a well known NP-hard problem, the Constrained Shortest Path problem, is studied. As efficient metaheuristic approaches are required for its solution, a new hybridized version of Particle Swarm Optimization algorithm with Variable Neighborhood Search is proposed for solving this significant combinatorial optimization problem. Particle Swarm Optimization (PSO) is a population-based swarm intelligence algorithm that simulates the social behavior of social organisms by using the physical movements of the particles in the swarm. A Variable Neighborhood Search (VNS) algorithm is applied in order to optimize the particles’ position. In the proposed algorithm, the Particle Swarm Optimization with combined Local and Global Expanding Neighborhood Topology (PSOLGENT), a different equation for the velocities of particles is given and a novel expanding neighborhood topology is used. Another issue in the application of the VNS algorithm in the Constrained Shortest Path problem is which local search algorithms are suitable from this problem. In this paper, a number of continuous local search algorithms are used. The algorithm is tested in a number of modified instances from the TSPLIB and comparisons with classic versions of PSO and with other versions of the proposed method are performed. Also, the results of the algorithm are compared with the results of a number of metaheuristic and evolutionary algorithms. The results obtained are very satisfactory and strengthen the efficiency of the algorithm. </efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="journal name">European Journal of Operational Research</efrbr-expression:note><efrbr-expression:note type="journal volume">261</efrbr-expression:note><efrbr-expression:note type="journal number">3</efrbr-expression:note><efrbr-expression:note type="page range">819-834</efrbr-expression:note></efrbr-expression:expression><efrbr-person:person identifier="http://users.isc.tuc.gr/~imarinakis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Marinakis Ioannis
            Μαρινακης Ιωαννης
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            Migdalas, Athanasios
         </efrbr-person:nameOfPerson></efrbr-person:person><efrbr-person:person identifier="http://viaf.org/viaf/293796199"><efrbr-person:nameOfPerson vocabulary="VIAF">
            Sifaleras, Angelo
         </efrbr-person:nameOfPerson></efrbr-person:person><efrbr-corporateBody:corporateBody identifier="http://www.elsevier.com/"><efrbr-corporateBody:nameOfTheCorporateBody vocabulary="S/R:PUBLISHERS">
            Elsevier
         </efrbr-corporateBody:nameOfTheCorporateBody></efrbr-corporateBody:corporateBody><efrbr-concept:concept identifier="B0A07568-21BC-4BB8-B635-5CB2AC79D930"><efrbr-concept:termForTheConcept>
            Constrained shortest path problem
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="3BE07507-C9E6-4F17-B3DC-5870039A3B07"><efrbr-concept:termForTheConcept>
            Expanding neighborhood topology
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="BEC78C20-D365-49B9-AB9B-E423DB543227"><efrbr-concept:termForTheConcept>
            Particle swarm optimization
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="7126B71A-3BD9-4886-8298-FEA932448690"><efrbr-concept:termForTheConcept>
            Variable neighborhood search
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