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http://hdl.handle.net/10609/90886
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Camp DC | Valor | Llengua/Idioma |
---|---|---|
dc.contributor.author | Guimarans, Daniel | - |
dc.contributor.author | Riera Terrén, Daniel | - |
dc.contributor.author | Juan, Angel A. | - |
dc.contributor.author | Ramos González, Juan José | - |
dc.contributor.other | Universitat Autònoma de Barcelona (UAB) | - |
dc.contributor.other | Universitat Oberta de Catalunya (UOC) | - |
dc.date.accessioned | 2019-01-30T13:35:03Z | - |
dc.date.available | 2019-01-30T13:35:03Z | - |
dc.date.issued | 2011-06 | - |
dc.identifier.citation | Guimarans, D., Herrero, R., Riera-Terrén, D., Juan, A.A. & Ramos, J. (2011). Combining probabilistic algorithms, Constraint Programming and Lagrangian Relaxation to solve the vehicle routing problem. Annals of Mathematics and Artificial Intelligence, 62(3), 299-315. doi: 10.1007/s10472-011-9261-y | - |
dc.identifier.issn | 1012-2443MIAR | - |
dc.identifier.uri | http://hdl.handle.net/10609/90886 | - |
dc.description.abstract | This paper presents an original hybrid approach to solve the Capacitated Vehicle Routing Problem (CVRP). The approach combines a Probabilistic Algorithm with Constraint Programming (CP) and Lagrangian Relaxation (LR). After introducing the CVRP and reviewing the existing literature on the topic, the paper proposes an approach based on a probabilistic Variable Neighbourhood Search (VNS) algorithm. Given a CVRP instance, this algorithm uses a randomized version of the classical Clarke and Wright Savings constructive heuristic to generate a starting solution. This starting solution is then improved through a local search process which combines: (a) LR to optimise each individual route, and (b) CP to quickly verify the feasibility of new proposed solutions. The efficiency of our approach is analysed after testing some well-known CVRP benchmarks. Benefits of our hybrid approach over already existing approaches are also discussed. In particular, the potential flexibility of our methodology is highlighted. | en |
dc.language.iso | eng | - |
dc.publisher | Annals of Mathematics and Artificial Intelligence | - |
dc.relation.ispartof | Annals of Mathematics and Artificial Intelligence, 2011, 62(3) | - |
dc.relation.uri | https://doi.org/10.1007/s10472-011-9261-y | - |
dc.rights | CC BY-NC-ND | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/es/ | - |
dc.subject | hybrid algorithms | en |
dc.subject | variable neighborhood search | en |
dc.subject | vehicle routing problem | en |
dc.subject | probabilistic algorithms | en |
dc.subject | algoritmos híbridos | es |
dc.subject | problema de rutas de vehículos | es |
dc.subject | algoritmos probabilísticos | es |
dc.subject | algorismes híbrids | ca |
dc.subject | problema de rutes de vehicles | ca |
dc.subject | algorismes probabilístics | ca |
dc.subject | búsqueda de vecindad variable | es |
dc.subject | cerca de veïnatge variable | ca |
dc.subject.lcsh | Algorithms | en |
dc.title | Combining probabilistic algorithms, Constraint Programming and Lagrangian Relaxation to solve the vehicle routing problem | - |
dc.type | info:eu-repo/semantics/article | - |
dc.subject.lemac | Algorismes | ca |
dc.subject.lcshes | Algoritmos | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
dc.identifier.doi | 10.1007/s10472-011-9261-y | - |
dc.gir.id | AR/0000002500 | - |
dc.relation.projectID | info:eu-repo/grantAgreement/HAROSA09 | - |
dc.type.version | info:eu-repo/semantics/submittedVersion | - |
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