Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem
The arc routing problem with a variable starting/ending position (Open Capacitated Arc Routing Problem - OCARP), in its classic version, pursues the best strategy to serve a set of customers located in the network arcs using vehicles. Compared to the Capacitated Arc Routing Problem (CARP), the OCARP...
- Autores:
-
Macias, B J
Amaya, C A
- Tipo de recurso:
- Fecha de publicación:
- 2016
- Institución:
- Universidad EAFIT
- Repositorio:
- Repositorio EAFIT
- Idioma:
- spa
- OAI Identifier:
- oai:repository.eafit.edu.co:10784/11282
- Acceso en línea:
- http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/3142
http://hdl.handle.net/10784/11282
- Palabra clave:
- Operations research
genetic algorithm
memetic algorithm
multi-objective optimization
CARP
OCARP
MO-OCARP
neural networks
local search
Operations Research
algoritmo genético
algoritmo memético
optimización multiobjetivo
CARP
OCARP
MO-OCARP
redes neuronales
búsqueda local
ruteo de vehículos sobre arcos.
90C08
90C35
90C29
90C59
68T20
- Rights
- License
- Copyright (c) 2016 Ingeniería y Ciencia | ing.cienc.
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2016-02-222017-04-03T16:10:26Z2016-02-222017-04-03T16:10:26Z2256-43141794–9165http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/3142http://hdl.handle.net/10784/1128210.17230/ingciencia.12.23.2The arc routing problem with a variable starting/ending position (Open Capacitated Arc Routing Problem - OCARP), in its classic version, pursues the best strategy to serve a set of customers located in the network arcs using vehicles. Compared to the Capacitated Arc Routing Problem (CARP), the OCARP lacks of constrains that guarantee that each vehicle ought to start and end the tour at a given vertex (also known as a depot). The aim of this paper is to propose a heuristic to find an efficient frontier for the main objective functions: minimize the number of vehicles and the total cost. Additionally, a hybrid algorithm that complements the genetic algorithm with artificial intelligence operator is proposed.El Problema de ruteo de vehículos sobre arcos con punto de inicio/fin variable (Open Capacitated Arc Routing Problem - OCARP), en su versión clásica, busca determinar la mejor estrategia para servir un conjunto de clientes localizados en los arcos de una red usando vehículos. A diferencia del Capacitated Arc Routing Problem (CARP), el OCARP no tiene las restricciones que aseguran que cada vehículo debe iniciar y terminar su ruta en un vértice dado (también conocido como depósito). El objetivo de este trabajo es proponer una heurística para encontrar la frontera eficiente dados dos objetivos: minimizar el número de vehículos y minimizar el costo total. Adicionalmente se propone complementar la heurística, la cual es basada en algoritmos genéticos, con operadores de inteligencia artificial.application/pdfspaUniversidad EAFIThttp://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/3142Copyright (c) 2016 Ingeniería y Ciencia | ing.cienc.http://creativecommons.org/licenses/by/4.0Acceso abiertohttp://purl.org/coar/access_right/c_abf2instname:Universidad EAFITreponame:Repositorio Institucional Universidad EAFITIngeniería y Ciencia | ing.cienc.; Vol 12, No 23 (2016); 25-46Ingeniería y Ciencia | ing.cienc.; Vol 12, No 23 (2016); 25-46Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing ProblemAlgoritmo memético con operadores de inteligencia artificial para el CARP con inicio y fin no determinado y bio-bjetivoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionarticlepublishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Operations researchgenetic algorithmmemetic algorithmmulti-objective optimizationCARPOCARPMO-OCARPneural networkslocal searchOperations Researchalgoritmo genéticoalgoritmo meméticooptimización multiobjetivoCARPOCARPMO-OCARPredes neuronalesbúsqueda localruteo de vehículos sobre arcos.90C0890C3590C2990C5968T20Macias, B JAmaya, C AIngeniería y Ciencia12232546ing.ciencORIGINALarticulo.htmlarticulo.htmlTexto completo HTMLtext/html290https://repository.eafit.edu.co/bitstreams/8f9e2d81-48d9-4cc5-a4d2-608502c48e84/download75ab54c8bd5ef15f24e24825b8a9cf38MD512.pdf2.pdfTexto completo PDFapplication/pdf659393https://repository.eafit.edu.co/bitstreams/0f67c90e-27e3-4cb9-9df1-4381238c17a7/download9fae27e3c1496d8e779d48b0951edfdcMD53THUMBNAILminaitura-ig_Mesa de trabajo 1.jpgminaitura-ig_Mesa de trabajo 1.jpgimage/jpeg265796https://repository.eafit.edu.co/bitstreams/db368318-d476-429c-875e-d9e54583e1ea/downloadda9b21a5c7e00c7f1127cef8e97035e0MD5210784/11282oai:repository.eafit.edu.co:10784/112822020-02-18 12:45:49.13open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.co |
| dc.title.eng.fl_str_mv |
Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem |
| dc.title.spa.fl_str_mv |
Algoritmo memético con operadores de inteligencia artificial para el CARP con inicio y fin no determinado y bio-bjetivo |
| title |
Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem |
| spellingShingle |
Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem Operations research genetic algorithm memetic algorithm multi-objective optimization CARP OCARP MO-OCARP neural networks local search Operations Research algoritmo genético algoritmo memético optimización multiobjetivo CARP OCARP MO-OCARP redes neuronales búsqueda local ruteo de vehículos sobre arcos. 90C08 90C35 90C29 90C59 68T20 |
| title_short |
Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem |
| title_full |
Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem |
| title_fullStr |
Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem |
| title_full_unstemmed |
Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem |
| title_sort |
Hybrid Algorithm Enhanced with Artificial Intelligence Applied to the Bi-Objective Open Capacitated Arc Routing Problem |
| dc.creator.fl_str_mv |
Macias, B J Amaya, C A |
| dc.contributor.author.none.fl_str_mv |
Macias, B J Amaya, C A |
| dc.subject.keyword.eng.fl_str_mv |
Operations research genetic algorithm memetic algorithm multi-objective optimization CARP OCARP MO-OCARP neural networks local search |
| topic |
Operations research genetic algorithm memetic algorithm multi-objective optimization CARP OCARP MO-OCARP neural networks local search Operations Research algoritmo genético algoritmo memético optimización multiobjetivo CARP OCARP MO-OCARP redes neuronales búsqueda local ruteo de vehículos sobre arcos. 90C08 90C35 90C29 90C59 68T20 |
| dc.subject.keyword.spa.fl_str_mv |
Operations Research algoritmo genético algoritmo memético optimización multiobjetivo CARP OCARP MO-OCARP redes neuronales búsqueda local ruteo de vehículos sobre arcos. 90C08 90C35 90C29 90C59 68T20 |
| description |
The arc routing problem with a variable starting/ending position (Open Capacitated Arc Routing Problem - OCARP), in its classic version, pursues the best strategy to serve a set of customers located in the network arcs using vehicles. Compared to the Capacitated Arc Routing Problem (CARP), the OCARP lacks of constrains that guarantee that each vehicle ought to start and end the tour at a given vertex (also known as a depot). The aim of this paper is to propose a heuristic to find an efficient frontier for the main objective functions: minimize the number of vehicles and the total cost. Additionally, a hybrid algorithm that complements the genetic algorithm with artificial intelligence operator is proposed. |
| publishDate |
2016 |
| dc.date.issued.none.fl_str_mv |
2016-02-22 |
| dc.date.available.none.fl_str_mv |
2017-04-03T16:10:26Z |
| dc.date.accessioned.none.fl_str_mv |
2017-04-03T16:10:26Z |
| dc.date.none.fl_str_mv |
2016-02-22 |
| dc.type.eng.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion article publishedVersion |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/resource_type/c_2df8fbb1 |
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Artículo |
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publishedVersion |
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2256-4314 1794–9165 |
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http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/3142 http://hdl.handle.net/10784/11282 |
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10.17230/ingciencia.12.23.2 |
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2256-4314 1794–9165 10.17230/ingciencia.12.23.2 |
| url |
http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/3142 http://hdl.handle.net/10784/11282 |
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spa |
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spa |
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http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/3142 |
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Copyright (c) 2016 Ingeniería y Ciencia | ing.cienc. http://creativecommons.org/licenses/by/4.0 |
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Acceso abierto |
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Copyright (c) 2016 Ingeniería y Ciencia | ing.cienc. http://creativecommons.org/licenses/by/4.0 Acceso abierto http://purl.org/coar/access_right/c_abf2 |
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Universidad EAFIT |
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Ingeniería y Ciencia | ing.cienc.; Vol 12, No 23 (2016); 25-46 |
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Ingeniería y Ciencia | ing.cienc.; Vol 12, No 23 (2016); 25-46 |
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