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Problema multiobjetivo de conformación de lotes, secuenciación y ruteo del picking, considerando múltiples operarios, vehículos con capacidad heterogénea, almacenes 3D multibloques, pedidos con llegadas dinámicas y fechas de entrega con ventanas de tiempo
dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional |
dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional |
dc.contributor.advisor | Correa Espinal, Alexander Alberto |
dc.contributor.advisor | Gómez Montoya, Rodrigo Andrés |
dc.contributor.author | Cano Arenas, José Alejandro |
dc.date.accessioned | 2020-07-27T21:59:41Z |
dc.date.available | 2020-07-27T21:59:41Z |
dc.date.issued | 2020-07-24 |
dc.identifier.citation | Cano, J.A. (2020). Problema multiobjetivo de conformación de lotes, secuenciación y ruteo del picking, considerando vehículos heterogéneos, almacenes 3D multibloques, pedidos con llegadas dinámicas y fechas de entrega con ventanas de tiempo. (Doctoral thesis), Universidad Nacional de Colombia - Sede Medellín, Colombia. |
dc.identifier.citation | Cano, J.A. (2020). Problema multiobjetivo de conformación de lotes, secuenciación y ruteo del picking, considerando vehículos heterogéneos, almacenes 3D multibloques, pedidos con llegadas dinámicas y fechas de entrega con ventanas de tiempo. (Tesis de Doctorado), Universidad Nacional de Colombia - Sede Medellín, Colombia. |
dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/77859 |
dc.description.abstract | This doctoral thesis aims to solve the multi-objective order batching, batch sequencing, batch assignment, and picker routing problem (PMCLSARP), considering heterogeneous vehicles, multi-block 3D warehouses, customer orders with dynamic arrivals (online) and due-windows. For this, a systematic literature review is performed to characterize the complexity and reality of order picking systems. Then, a mathematical formulation is proposed for the PMCLSARP, showing this problem is classified as NP-Hard due to its complexity. To solve the online PMCLSARP, an algorithm called AGOG + AGOI is designed and developed by nesting two genetic algorithms, and the parameters of these algorithms are validated to find the combination that provides the best performance for the objective function and computing time. The performance of the AGOG + AGOI is validated through different experimental scenarios and it is compared with the results provided by two benchmarks, obtaining average savings in the objective function of 25.2% and 18.6% when comparing AGOG + AGOI with the algorithms FCFS-SS3D and EDD-SS3D respectively. Consequently, the AGOG + AGOI provides satisfactory solutions for warehouse operating environments regarding operational efficiency (picking time), customer service (tardiness and earliness), and reasonable computing time, which can vary between 34 seconds and 2,8 minutes for each run of the algorithm. |
dc.description.abstract | Esta tesis de doctorado tiene como objetivo solucionar el problema multiobjetivo de conformación de lotes, secuenciación, asignación y ruteo del picking (PMCLSARP), considerando vehículos heterogéneos, almacenes 3D multibloques, pedidos con llegadas dinámicas (en línea) y fechas de entrega con ventanas de tiempo. Para esto, se realizó una revisión sistemática de la literatura que caracterizó los componentes principales para una aproximación a la complejidad y realidad de la preparación de pedidos (picking) en almacenes y centros de distribución. A través de la formulación matemática del PMCLSARP se logra la modelación del problema a abordar en la tesis, el cual se clasifica como NP-Hard debido a su complejidad. Para solucionar el PMCLSARP en línea, se diseña y desarrolla un algoritmo denominado AGOG+AGOI que anida dos algoritmos genéticos, y a dichos algoritmos se les realiza una validación de parámetros para encontrar la combinación que brinde mejor desempeño para la función objetivo y tiempos de computación. El desempeño del AGOG+AGOI se valida a través de diferentes escenarios de operación de almacenes y centros de distribución, y se compara con los resultados obtenidos con dos puntos de referencia, obteniendo ahorros promedio en la función objetivo del 25,2% y 18,6% al comparar el AGOG+AGOI con los algoritmos FCFS-SS3D y EDD-SS3D, respectivamente. Por lo tanto, el AGOG+AGOI brinda soluciones satisfactorias en eficiencia operativa (tiempo de picking) y servicio al cliente (tardanza y prontitud), y en tiempos de computación razonables para ambientes operativos de almacén, que pueden variar entre 34 segundos y 2,8 minutos para cada corrida del AGOG+AGOI. |
dc.format.extent | 165 |
dc.format.mimetype | application/pdf |
dc.language.iso | spa |
dc.rights | Derechos reservados - Universidad Nacional de Colombia |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.subject.ddc | 620 - Ingeniería y operaciones afines |
dc.subject.ddc | 620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería |
dc.title | Problema multiobjetivo de conformación de lotes, secuenciación y ruteo del picking, considerando múltiples operarios, vehículos con capacidad heterogénea, almacenes 3D multibloques, pedidos con llegadas dinámicas y fechas de entrega con ventanas de tiempo |
dc.title.alternative | Multi-objective order batching, sequencing and routing picking problem considering on-line orders, multiple pickers, heterogeneous vehicles, multi-block 3D warehouses, and due-windows |
dc.type | Otro |
dc.rights.spa | Acceso abierto |
dc.type.driver | info:eu-repo/semantics/other |
dc.type.version | info:eu-repo/semantics/acceptedVersion |
dc.publisher.program | Medellín - Minas - Doctorado en Ingeniería - Industria y Organizaciones |
dc.contributor.corporatename | Universidad Nacional de Colombia - Sede Medellín |
dc.contributor.researchgroup | MODELAMIENTO PARA LA GESTIÓN DE OPERACIONES (GIMGO) |
dc.description.degreelevel | Doctorado |
dc.publisher.department | Departamento de Ingeniería de la Organización |
dc.publisher.branch | Universidad Nacional de Colombia - Sede Medellín |
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dc.rights.accessrights | info:eu-repo/semantics/openAccess |
dc.subject.proposal | order picking |
dc.subject.proposal | ruteo del picking |
dc.subject.proposal | order batching |
dc.subject.proposal | picking |
dc.subject.proposal | algoritmos genéticos |
dc.subject.proposal | picker routing |
dc.subject.proposal | gestión de almacenes |
dc.subject.proposal | genetic algorithms |
dc.subject.proposal | Modelo multiobjetivo |
dc.subject.proposal | warehouse management |
dc.type.coar | http://purl.org/coar/resource_type/c_1843 |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa |
dc.type.content | Text |
oaire.accessrights | http://purl.org/coar/access_right/c_abf2 |
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