REPOSITORIO
INSTITUCIONAL

    • español
    • English
  • Site map
  • English 
    • español
    • English
  • Login
  • Artículos(current)
  • Libros
  • Tesis
  • Trabajos de grado
  • Documentos Institucionales
    • Actas
    • Acuerdos
    • Decretos
    • Resoluciones
  • Multimedia
  • Productos de investigación
  • Acerca de
View Item 
  •   Home
  • Artículos
  • Indexados Scopus
  • View Item
  •   Home
  • Artículos
  • Indexados Scopus
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

A discrete particle swarm optimization to solve the put-away routing problem in distribution centres

Thumbnail
Share this
Author
Gómez-Montoya R.A.
Cano J.A.
Cortés P.
Salazar F.
TY - GEN T1 - A discrete particle swarm optimization to solve the put-away routing problem in distribution centres AU - Gómez-Montoya R.A. AU - Cano J.A. AU - Cortés P. AU - Salazar F. UR - http://hdl.handle.net/11407/5907 PB - MDPI AG AB - Put-away operations typically consist of moving products from depots to allocated storage locations using either operators or Material Handling Equipment (MHE), accounting for important operative costs in warehouses and impacting operations efficiency. Therefore, this paper aims to formulate and solve a Put-away Routing Problem (PRP) in distribution centres (DCs). This PRP formulation represents a novel approach due to the consideration of a fleet of homogeneous Material Handling Equipment (MHE), heterogeneous products linked to a put-away list size, depot location and multi-parallel aisles in a distribution centre. It should be noted that the slotting problem, rather than the PRP, has usually been studied in the literature, whereas the PRP is addressed in this paper. The PRP is solved using a discrete particle swarm optimization (PSO) algorithm that is compared to tabu search approaches (Classical Tabu Search (CTS), Tabu Search (TS) 2-Opt) and an empirical rule. As a result, it was found that a discrete PSO generates the best solutions, as the time savings range from 2 to 13% relative to CTS and TS 2-Opt for different combinations of factor levels evaluated in the experimentation. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. ER - @misc{11407_5907, author = {Gómez-Montoya R.A. and Cano J.A. and Cortés P. and Salazar F.}, title = {A discrete particle swarm optimization to solve the put-away routing problem in distribution centres}, year = {}, abstract = {Put-away operations typically consist of moving products from depots to allocated storage locations using either operators or Material Handling Equipment (MHE), accounting for important operative costs in warehouses and impacting operations efficiency. Therefore, this paper aims to formulate and solve a Put-away Routing Problem (PRP) in distribution centres (DCs). This PRP formulation represents a novel approach due to the consideration of a fleet of homogeneous Material Handling Equipment (MHE), heterogeneous products linked to a put-away list size, depot location and multi-parallel aisles in a distribution centre. It should be noted that the slotting problem, rather than the PRP, has usually been studied in the literature, whereas the PRP is addressed in this paper. The PRP is solved using a discrete particle swarm optimization (PSO) algorithm that is compared to tabu search approaches (Classical Tabu Search (CTS), Tabu Search (TS) 2-Opt) and an empirical rule. As a result, it was found that a discrete PSO generates the best solutions, as the time savings range from 2 to 13% relative to CTS and TS 2-Opt for different combinations of factor levels evaluated in the experimentation. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.}, url = {http://hdl.handle.net/11407/5907} }RT Generic T1 A discrete particle swarm optimization to solve the put-away routing problem in distribution centres A1 Gómez-Montoya R.A. A1 Cano J.A. A1 Cortés P. A1 Salazar F. LK http://hdl.handle.net/11407/5907 PB MDPI AG AB Put-away operations typically consist of moving products from depots to allocated storage locations using either operators or Material Handling Equipment (MHE), accounting for important operative costs in warehouses and impacting operations efficiency. Therefore, this paper aims to formulate and solve a Put-away Routing Problem (PRP) in distribution centres (DCs). This PRP formulation represents a novel approach due to the consideration of a fleet of homogeneous Material Handling Equipment (MHE), heterogeneous products linked to a put-away list size, depot location and multi-parallel aisles in a distribution centre. It should be noted that the slotting problem, rather than the PRP, has usually been studied in the literature, whereas the PRP is addressed in this paper. The PRP is solved using a discrete particle swarm optimization (PSO) algorithm that is compared to tabu search approaches (Classical Tabu Search (CTS), Tabu Search (TS) 2-Opt) and an empirical rule. As a result, it was found that a discrete PSO generates the best solutions, as the time savings range from 2 to 13% relative to CTS and TS 2-Opt for different combinations of factor levels evaluated in the experimentation. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. OL Spanish (121)
Gestores bibliográficos
Refworks
Zotero
BibTeX
CiteULike
Metadata
Show full item record
Abstract
Put-away operations typically consist of moving products from depots to allocated storage locations using either operators or Material Handling Equipment (MHE), accounting for important operative costs in warehouses and impacting operations efficiency. Therefore, this paper aims to formulate and solve a Put-away Routing Problem (PRP) in distribution centres (DCs). This PRP formulation represents a novel approach due to the consideration of a fleet of homogeneous Material Handling Equipment (MHE), heterogeneous products linked to a put-away list size, depot location and multi-parallel aisles in a distribution centre. It should be noted that the slotting problem, rather than the PRP, has usually been studied in the literature, whereas the PRP is addressed in this paper. The PRP is solved using a discrete particle swarm optimization (PSO) algorithm that is compared to tabu search approaches (Classical Tabu Search (CTS), Tabu Search (TS) 2-Opt) and an empirical rule. As a result, it was found that a discrete PSO generates the best solutions, as the time savings range from 2 to 13% relative to CTS and TS 2-Opt for different combinations of factor levels evaluated in the experimentation. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
URI
http://hdl.handle.net/11407/5907
Collections
  • Indexados Scopus [1337]
All of RI UdeMCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
My AccountLoginRegister
Statistics GTMSee Statistics GTM
OFERTA ACADÉMICA
  • Oferta académica completa
  • Facultad de Derecho
  • Facultad de Comunicación
  • Facultad de Ingenierías
  • Facultad de Ciencias Económicas y Administrativas
  • Facultad de Ciencias Sociales y Humanas
  • Facultad de Ciencias Básicas
  • Facultad de Diseño
SERVICIOS
  • Teatro
  • Educación continuada
  • Centro de Idiomas
  • Consultorio Jurídico
  • Centro de Asesorías y Consultorías
  • Prácticas empresariales
  • Operadora Profesional de Certámenes
INVESTIGACIÓN
  • Centros de investigación
  • Revistas científicas
  • Repositorio institucional
  • Universidad - Empresa - Estado - Sociedad

Universidad de Medellín - Teléfono: +57 (4) 590 4500 Ext. 11422 - Dirección: Carrera 87 N° 30 - 65 Medellín - Colombia - Suramérica
© Copyright 2012 ® Todos los Derechos Reservados
Contacto

 infotegra.com