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dc.contributor.authorPedrola Escribà, Òscar
dc.contributor.authorRuiz Ramírez, Marc
dc.contributor.authorVelasco Esteban, Luis Domingo
dc.contributor.authorCareglio, Davide
dc.contributor.authorGonzález de Dios, Óscar
dc.contributor.authorComellas Colomé, Jaume
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2013-11-13T18:41:41Z
dc.date.created2013-12
dc.date.issued2013-12
dc.identifier.citationPedrola, O. [et al.]. A GRASP with path-relinking heuristic for the survivable IP/MPLS-over-WSON multi-layer network optimization problem. "Computers & operations research", Desembre 2013, vol. 40, núm. 12, p. 3174-3187.
dc.identifier.issn0305-0548
dc.identifier.urihttp://hdl.handle.net/2117/20600
dc.description.abstractIn this paper we deal with the survivable internet protocol (IP)/multi-protocol label switching (MPLS)-over-wavelength switched optical network (WSON) multi-layer network optimization problem (SIMNO). This problem entails planning an IP/MPLS network layer over a photonic mesh infrastructure whilst, at the same time, ensuring the highest availability of services and minimizing the capital expenditures (CAPEX) investments. Such a problem is currently identified as an open issue among network operators, and hence, its solution is of great interest. To tackle SIMNO, we first provide an integer linear programming (ILP) formulation which provides an insight into the complexity of its managing. Then, a greedy randomized adaptive search procedure (GRASP) with path-relinking (PR) together with a biased random-key genetic algorithm (BRKGA) are specifically developed to help solve the problem. The performance of both heuristics is exhaustively tested and compared making use of various network and traffic instances. Numerical experiments show the benefits of using GRASP instead of BRKGA when dealing with highly complex network scenarios. Moreover, we verified that the use of GRASP with PR remarkably improves the basic GRASP algorithm, particularly in real-sized, complex scenarios such as those proposed in this paper.
dc.format.extent14 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telecomunicació òptica
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
dc.subject.lcshComputer networks
dc.subject.otherBiased random-key genetic algorithm (BRKGA)
dc.subject.otherGreedy randomized adaptive search procedure (GRASP)
dc.subject.otherMulti-layer optimization
dc.subject.otherPath-relinking (PR)
dc.subject.otherSurvivability
dc.titleA GRASP with path-relinking heuristic for the survivable IP/MPLS-over-WSON multi-layer network optimization problem
dc.typeArticle
dc.subject.lemacOrdinadors, Xarxes d'
dc.contributor.groupUniversitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla
dc.contributor.groupUniversitat Politècnica de Catalunya. GCO - Grup de Comunicacions Òptiques
dc.identifier.doi10.1016/j.cor.2011.10.026
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0305054811003145
dc.rights.accessRestricted access - publisher's policy
drac.iddocument12884258
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/247674/EU/Scalable, Tunable and Resilient Optical Networks Guaranteeing Extremely-high Speed Transport/STRONGEST
dc.date.lift10000-01-01
upcommons.citation.authorPedrola, O.; Ruiz, M.; Velasco, L.; Careglio, D.; Gonzalez , O.; Comellas, J.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameComputers & operations research
upcommons.citation.volume40
upcommons.citation.number12
upcommons.citation.startingPage3174
upcommons.citation.endingPage3187


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Spain