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dc.contributor.authoramelec, viloriaspa
dc.contributor.authorLizardo Zelaya, Nelson Albertospa
dc.contributor.authorVarela, Noelspa
dc.date.accessioned2021-01-05T14:33:11Z
dc.date.available2021-01-05T14:33:11Z
dc.date.issued2020
dc.identifier.issn1646-9895spa
dc.identifier.urihttps://hdl.handle.net/11323/7658spa
dc.description.abstractThe design of efficient routes for vehicles visiting a significant number of destinations is a critical factor for the competitiveness of many companies. The design of such routes is known as the vehicle routing problem. Indeed, efficient vehicle routing is one of the most studied problems in the areas of logistics and combinatorial optimization. The present study presents a memetic algorithm that evolves using a mechanism inspired by virus mutations. Additionally, the algorithm uses Taboo Search as an intensification mechanism.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoeng
dc.publisherCorporación Universidad de la Costaspa
dc.rightsCC0 1.0 Universalspa
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/spa
dc.sourceProcedia Computer Sciencespa
dc.subjectThe problem of routing vehiclesspa
dc.subjectLimited capacityspa
dc.subjectMemetic algorithmspa
dc.titleSearch for optimal routes on roads applying metaheuristic algorithmsspa
dc.typeArtículo de revistaspa
dc.source.urlhttps://www.sciencedirect.com/science/article/pii/S1877050920317440spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doihttps://doi.org/10.1016/j.procs.2020.07.063spa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.relation.references[1] Peng, B., Zhang, Y., Lü, Z., Cheng, T. C. E., & Glover, F. (2020). A learning-based memetic algorithm for the multiple vehicle pickup and delivery problem with LIFO loading. Computers & Industrial Engineering, 142, 106241.spa
dc.relation.references[2] Yağmur, E., & Kesen, S. E. (2020). A memetic algorithm for joint production and distribution scheduling with due dates. Computers & Industrial Engineering, 142, 106342.spa
dc.relation.references[3] Li, X., Shi, X., Zhao, Y., Liang, H., & Dong, Y. (2020). SVND Enhanced Metaheuristic for Plug-In Hybrid Electric Vehicle Routing Problem. Applied Sciences, 10(2), 441.spa
dc.relation.references[4] Wan, J., Chen, X., & Li, R. (2020). Improved Memetic Algorithm for Multi-depot Multi-objective Capacitated Arc Routing Problem. In MATEC Web of Conferences (Vol. 308, p. 01002). EDP Sciences.spa
dc.relation.references[5] Mor, A., & Speranza, M. G. (2020). Vehicle routing problems over time: a survey. 4OR, 1-21.spa
dc.relation.references[6] Nosrati, M., & Khamseh, A. (2020). Bi objective hybrid vehicle routing problem with alternative paths and reliability. Decision Science Letters, 9(2), 145-162.spa
dc.relation.references[7] Deng, J., & Wang, L. (2017). A competitive memetic algorithm for multi-objective distributed permutation flow shop scheduling problem. Swarm and evolutionary computation, 32, 121-131.spa
dc.relation.references[8] Duran-Micco, J., Vermeir, E., & Vansteenwegen, P. (2020). Considering emissions in the transit network design and frequency setting problem with a heterogeneous fleet. European Journal of Operational Research, 282(2), 580-592.spa
dc.relation.references[9] Neira, D. A., Aguayo, M. M., & Klapp, M. A. (2020). New compact integer programming formulations for the multi-trip vehicle routing problem with time windows. Computers & Industrial Engineering, 106399.spa
dc.relation.references[10] Smiti, N., Dhiaf, M. M., Jarboui, B., & Hanafi, S. (2020). Skewed general variable neighborhood search for the cumulative capacitated vehicle routing problem. International Transactions in Operational Research, 27(1), 651-664.spa
dc.relation.references[11] M’Hallah, R. (2020). Combining Exact Methods to Construct Effective Hybrid Approaches to Vehicle Routing. In Women in Industrial and Systems Engineering (pp. 435-456). Springer, Cham.spa
dc.relation.references[12] Blocho, M. (2020). Parallel algorithms for solving rich vehicle routing problems. In Smart Delivery Systems (pp. 185-201). Elsevier.spa
dc.relation.references[13] Molina, J. C., Salmeron, J. L., & Eguia, I. (2020). An ACS-based Memetic algorithm for the Heterogeneous Vehicle Routing Problem with time windows. Expert Systems with Applications, 113379.spa
dc.relation.references[14] Ghosh, M., Begum, S., Sarkar, R., Chakraborty, D., & Maulik, U. (2019). Recursive memetic algorithm for gene selection in microarray data. Expert Systems with Applications, 116, 172-185.spa
dc.relation.references[15] Viloria, A., Guerrero, I. M., Caraballo, H. M., Llinas, N. O., Valero, L., Palma, H. H., … Lezama, O. B. P. (2019). Effect on the demand and stock returns: Cross-sectional of big data and time-series analysis. In Communications in Computer and Information Science (Vol. 1122 CCIS, pp. 211–220). Springer. https://doi.org/10.1007/978-981-15-1301-5_17spa
dc.relation.references[16] Viloria, A., Crissien Borrero, T., Vargas Villa, J., Torres, M., García Guiliany, J., Vargas Mercado, C., … Batista Zea, K. (2019). Differential evolution clustering and data mining for determining learning routes in moodle. In Communications in Computer and Information Science (Vol. 1071, pp. 170–178). Springer Verlag. https://doi.org/10.1007/978-981-32-9563-6_18spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


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