Multiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windows

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The delivery of products on time while reducing transportation costs has become an issue for retail companies in Latin America due to the rise of the e-commerce market in recent years. The Vehicle Routing Problem (VRP) is one of the most studied topics in operations research. This work addresses the...

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Detalles Bibliográficos
Autores: Huamán, Airton, Huancahuari, Marco, Wong, Lenis
Formato: artículo
Fecha de Publicación:2022
Institución:Universidad Peruana de Ciencias Aplicadas
Repositorio:UPC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorioacademico.upc.edu.pe:10757/660094
Enlace del recurso:http://hdl.handle.net/10757/660094
Nivel de acceso:acceso embargado
Materia:Ant colony optimization
Capacitated vehicle routing problem with time windows
K-means
Vehicle routing problem
Vehicle scheduling problem
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network_acronym_str UUPC
network_name_str UPC-Institucional
repository_id_str 2670
dc.title.es_PE.fl_str_mv Multiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windows
title Multiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windows
spellingShingle Multiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windows
Huamán, Airton
Ant colony optimization
Capacitated vehicle routing problem with time windows
K-means
Vehicle routing problem
Vehicle scheduling problem
title_short Multiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windows
title_full Multiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windows
title_fullStr Multiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windows
title_full_unstemmed Multiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windows
title_sort Multiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windows
author Huamán, Airton
author_facet Huamán, Airton
Huancahuari, Marco
Wong, Lenis
author_role author
author2 Huancahuari, Marco
Wong, Lenis
author2_role author
author
dc.contributor.author.fl_str_mv Huamán, Airton
Huancahuari, Marco
Wong, Lenis
dc.subject.es_PE.fl_str_mv Ant colony optimization
Capacitated vehicle routing problem with time windows
K-means
Vehicle routing problem
Vehicle scheduling problem
topic Ant colony optimization
Capacitated vehicle routing problem with time windows
K-means
Vehicle routing problem
Vehicle scheduling problem
description The delivery of products on time while reducing transportation costs has become an issue for retail companies in Latin America due to the rise of the e-commerce market in recent years. The Vehicle Routing Problem (VRP) is one of the most studied topics in operations research. This work addresses the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). The problem focuses on finding optimal routes for each vehicle to serve customers on time and minimal transportation costs under capacity and time constraints. Previous research has addressed the issue by proposing non-exact and exact techniques. This paper aims to select a proper approach and algorithms to present a model to solve the CVRPTW in real-world scenarios by incorporating a Google distance matrix, the empirical knowledge of delivery zones, and a solution relatively easy to deploy in a cloud environment. The proposed model consists of four phases: order scheduling, client clustering, delivery route generation, and operator assignment. We use the K-means algorithm to cluster customers and assign them to vehicles and the Ant Colony Optimization (ACO) algorithm to generate optimal routes. The proposed model was validated through a case study for a retail company in Lima, Perú. The results show that the proposed model reduces the route generation execution time by 95% of the average time. It also cuts travel distance and time by around 182 km and 532 min in 5-day periods.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-06-03T16:20:56Z
dc.date.available.none.fl_str_mv 2022-06-03T16:20:56Z
dc.date.issued.fl_str_mv 2022-01-01
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/article
dc.type.other.es_PE.fl_str_mv Articulo científico
format article
dc.identifier.issn.none.fl_str_mv 18650929
dc.identifier.doi.none.fl_str_mv 10.1007/978-3-031-04447-2_10
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10757/660094
dc.identifier.eissn.none.fl_str_mv 18650937
dc.identifier.journal.es_PE.fl_str_mv Communications in Computer and Information Science
dc.identifier.eid.none.fl_str_mv 2-s2.0-85128946489
dc.identifier.scopusid.none.fl_str_mv SCOPUS_ID:85128946489
dc.identifier.isni.none.fl_str_mv 0000 0001 2196 144X
identifier_str_mv 18650929
10.1007/978-3-031-04447-2_10
18650937
Communications in Computer and Information Science
2-s2.0-85128946489
SCOPUS_ID:85128946489
0000 0001 2196 144X
url http://hdl.handle.net/10757/660094
dc.language.iso.es_PE.fl_str_mv eng
language eng
dc.relation.url.es_PE.fl_str_mv https://link.springer.com/chapter/10.1007/978-3-031-04447-2_10
dc.rights.es_PE.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
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dc.publisher.es_PE.fl_str_mv Springer Science and Business Media Deutschland GmbH
dc.source.es_PE.fl_str_mv Universidad Peruana de Ciencias Aplicadas (UPC)
Repositorio Académico - UPC
dc.source.none.fl_str_mv reponame:UPC-Institucional
instname:Universidad Peruana de Ciencias Aplicadas
instacron:UPC
instname_str Universidad Peruana de Ciencias Aplicadas
instacron_str UPC
institution UPC
reponame_str UPC-Institucional
collection UPC-Institucional
dc.source.journaltitle.none.fl_str_mv Communications in Computer and Information Science
dc.source.volume.none.fl_str_mv 1577 CCIS
dc.source.beginpage.none.fl_str_mv 141
dc.source.endpage.none.fl_str_mv 157
bitstream.url.fl_str_mv https://repositorioacademico.upc.edu.pe/bitstream/10757/660094/1/license.txt
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spelling 2062ca47657d4766f00b3733ebfba6fc30082168270898273e207a4c1c6735b25e3300f1524a3bbf68b7e2680e1ab2f7ba0bfd300Huamán, AirtonHuancahuari, MarcoWong, Lenis2022-06-03T16:20:56Z2022-06-03T16:20:56Z2022-01-011865092910.1007/978-3-031-04447-2_10http://hdl.handle.net/10757/66009418650937Communications in Computer and Information Science2-s2.0-85128946489SCOPUS_ID:851289464890000 0001 2196 144XThe delivery of products on time while reducing transportation costs has become an issue for retail companies in Latin America due to the rise of the e-commerce market in recent years. The Vehicle Routing Problem (VRP) is one of the most studied topics in operations research. This work addresses the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). The problem focuses on finding optimal routes for each vehicle to serve customers on time and minimal transportation costs under capacity and time constraints. Previous research has addressed the issue by proposing non-exact and exact techniques. This paper aims to select a proper approach and algorithms to present a model to solve the CVRPTW in real-world scenarios by incorporating a Google distance matrix, the empirical knowledge of delivery zones, and a solution relatively easy to deploy in a cloud environment. The proposed model consists of four phases: order scheduling, client clustering, delivery route generation, and operator assignment. We use the K-means algorithm to cluster customers and assign them to vehicles and the Ant Colony Optimization (ACO) algorithm to generate optimal routes. The proposed model was validated through a case study for a retail company in Lima, Perú. The results show that the proposed model reduces the route generation execution time by 95% of the average time. It also cuts travel distance and time by around 182 km and 532 min in 5-day periods.application/htmlengSpringer Science and Business Media Deutschland GmbHhttps://link.springer.com/chapter/10.1007/978-3-031-04447-2_10info:eu-repo/semantics/embargoedAccessUniversidad Peruana de Ciencias Aplicadas (UPC)Repositorio Académico - UPCCommunications in Computer and Information Science1577 CCIS141157reponame:UPC-Institucionalinstname:Universidad Peruana de Ciencias Aplicadasinstacron:UPCAnt colony optimizationCapacitated vehicle routing problem with time windowsK-meansVehicle routing problemVehicle scheduling problemMultiphase model based on K-means and ant colony optimization to solve the capacitated vehicle routing problem with time windowsinfo:eu-repo/semantics/articleArticulo científicoLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorioacademico.upc.edu.pe/bitstream/10757/660094/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD51false10757/660094oai:repositorioacademico.upc.edu.pe:10757/6600942022-10-20 13:02:07.358Repositorio académico upcupc@openrepository.comTk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo=
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