An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods
The effective distribution of perishable food items is a critical aspect of managing the food industry's supply chain, given their physical–chemical, biological characteristics and composition, which make them highly susceptible to rapid deterioration. This research presents a transport model i...
- Autores:
-
Acevedo-Chedid, Jaime
Soto, Melissa Caro
Ospina-Mateus, Holman
Salas-Navarro, Katherinne
Sana, Shib Sankar
- Tipo de recurso:
- Fecha de publicación:
- 2023
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/12261
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12261
https://doi.org/10.1007/s12063-023-00379-8
- Palabra clave:
- Time Windows;
Pickup and Delivery;
Dynamic Routing
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.spa.fl_str_mv |
An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods |
title |
An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods |
spellingShingle |
An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods Time Windows; Pickup and Delivery; Dynamic Routing LEMB |
title_short |
An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods |
title_full |
An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods |
title_fullStr |
An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods |
title_full_unstemmed |
An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods |
title_sort |
An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods |
dc.creator.fl_str_mv |
Acevedo-Chedid, Jaime Soto, Melissa Caro Ospina-Mateus, Holman Salas-Navarro, Katherinne Sana, Shib Sankar |
dc.contributor.author.none.fl_str_mv |
Acevedo-Chedid, Jaime Soto, Melissa Caro Ospina-Mateus, Holman Salas-Navarro, Katherinne Sana, Shib Sankar |
dc.subject.keywords.spa.fl_str_mv |
Time Windows; Pickup and Delivery; Dynamic Routing |
topic |
Time Windows; Pickup and Delivery; Dynamic Routing LEMB |
dc.subject.armarc.none.fl_str_mv |
LEMB |
description |
The effective distribution of perishable food items is a critical aspect of managing the food industry's supply chain, given their physical–chemical, biological characteristics and composition, which make them highly susceptible to rapid deterioration. This research presents a transport model incorporating a cross-dock system to efficiently deliver goods from production plants to markets. The model incorporates a vehicle routing model that considers time windows for pick-ups and deliveries, optimal cross-dock center locations, a heterogeneous vehicle fleet of limited capacity, and scheduling product collections, arrivals, and departures. The model is a mixed-integer non-linear optimization model that effectively minimizes logistics costs and environmental impacts by considering various parameters such as speed, waiting times, loading and unloading times, and costs associated with the entire operation. The findings demonstrate that the cross-dock structure is highly conducive to distributing perishable goods, achieved by minimizing collection and distribution operations, adhering to designated time windows, and efficiently allocating resources. The GAMS 23.6.5 software is used to program the model, employing various solution strategies, including experimental tests with scenarios, as well as the "posterior," "Pareto optimization," and "weighted sum" methods. The case study in Sincelejo (Sucre, Colombia) reported the best solution, representing 60% of logistics and 40% of environmental costs. The results show complete compliance with routes, no inventory generation, and the necessity of two inbounds and two outbound vehicles for collection from suppliers and delivery to retailers. This study presents an efficient model for managing the transportation of perishable goods, contributing to sustainable distribution activities, and environmental conservation in the food industry's supply chain. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. |
publishDate |
2023 |
dc.date.accessioned.none.fl_str_mv |
2023-07-21T15:33:23Z |
dc.date.available.none.fl_str_mv |
2023-07-21T15:33:23Z |
dc.date.issued.none.fl_str_mv |
2023 |
dc.date.submitted.none.fl_str_mv |
2023 |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_b1a7d7d4d402bcce |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
dc.type.hasversion.spa.fl_str_mv |
info:eu-repo/semantics/draft |
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http://purl.org/coar/resource_type/c_6501 |
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draft |
dc.identifier.citation.spa.fl_str_mv |
Acevedo-Chedid, J., Soto, M.C., Ospina-Mateus, H. et al. An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods. Oper Manag Res (2023). https://doi.org/10.1007/s12063-023-00379-8 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/12261 |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1007/s12063-023-00379-8 |
dc.identifier.instname.spa.fl_str_mv |
Universidad Tecnológica de Bolívar |
dc.identifier.reponame.spa.fl_str_mv |
Repositorio Universidad Tecnológica de Bolívar |
identifier_str_mv |
Acevedo-Chedid, J., Soto, M.C., Ospina-Mateus, H. et al. An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods. Oper Manag Res (2023). https://doi.org/10.1007/s12063-023-00379-8 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
url |
https://hdl.handle.net/20.500.12585/12261 https://doi.org/10.1007/s12063-023-00379-8 |
dc.language.iso.spa.fl_str_mv |
eng |
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eng |
dc.rights.coar.fl_str_mv |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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Cartagena de Indias |
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Universidad Tecnológica de Bolívar |
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Acevedo-Chedid, Jaime55848f44-62b2-463a-8a80-58f6a2819afeSoto, Melissa Caro235d26be-5797-4d73-b7aa-d5cdc5e4ea3bOspina-Mateus, Holman1b4b1bc0-3606-4c14-bb13-dbc9d4251891Salas-Navarro, Katherinneb358d582-e66b-4c09-8f7e-34b116ff94aeSana, Shib Sankare81af3d1-9873-434c-8df4-41a1929550652023-07-21T15:33:23Z2023-07-21T15:33:23Z20232023Acevedo-Chedid, J., Soto, M.C., Ospina-Mateus, H. et al. An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods. Oper Manag Res (2023). https://doi.org/10.1007/s12063-023-00379-8https://hdl.handle.net/20.500.12585/12261https://doi.org/10.1007/s12063-023-00379-8Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe effective distribution of perishable food items is a critical aspect of managing the food industry's supply chain, given their physical–chemical, biological characteristics and composition, which make them highly susceptible to rapid deterioration. This research presents a transport model incorporating a cross-dock system to efficiently deliver goods from production plants to markets. The model incorporates a vehicle routing model that considers time windows for pick-ups and deliveries, optimal cross-dock center locations, a heterogeneous vehicle fleet of limited capacity, and scheduling product collections, arrivals, and departures. The model is a mixed-integer non-linear optimization model that effectively minimizes logistics costs and environmental impacts by considering various parameters such as speed, waiting times, loading and unloading times, and costs associated with the entire operation. The findings demonstrate that the cross-dock structure is highly conducive to distributing perishable goods, achieved by minimizing collection and distribution operations, adhering to designated time windows, and efficiently allocating resources. The GAMS 23.6.5 software is used to program the model, employing various solution strategies, including experimental tests with scenarios, as well as the "posterior," "Pareto optimization," and "weighted sum" methods. The case study in Sincelejo (Sucre, Colombia) reported the best solution, representing 60% of logistics and 40% of environmental costs. The results show complete compliance with routes, no inventory generation, and the necessity of two inbounds and two outbound vehicles for collection from suppliers and delivery to retailers. This study presents an efficient model for managing the transportation of perishable goods, contributing to sustainable distribution activities, and environmental conservation in the food industry's supply chain. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.application/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Operations Management ResearchAn optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foodsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Time Windows;Pickup and Delivery;Dynamic RoutingLEMBCartagena de IndiasAgi, M.A.N., Soni, H.N. Joint pricing and inventory decisions for perishable products with age-, stock-, and price-dependent demand rate (2020) Journal of the Operational Research Society, 71 (1), pp. 85-99. Cited 36 times. https://www.tandfonline.com/loi/tjor20 doi: 10.1080/01605682.2018.1525473Agrawal, A.K., Yadav, S., Gupta, A.A., Pandey, S. A genetic algorithm model for optimizing vehicle routing problems with perishable products under time-window and quality requirements (2022) Decision Analytics Journal, 5, art. no. 100139. Cited 7 times. https://www.journals.elsevier.com/decision-analytics-journal doi: 10.1016/j.dajour.2022.100139Agustina, D., Lee, C.K.M., Piplani, R. Vehicle scheduling and routing at a cross docking center for food supply chains (2014) International Journal of Production Economics, 152, pp. 29-41. Cited 118 times. doi: 10.1016/j.ijpe.2014.01.002Ahkamiraad, A., Wang, Y. Capacitated and multiple cross-docked vehicle routing problem with pickup, delivery, and time windows (2018) Computers and Industrial Engineering, 119, pp. 76-84. Cited 45 times. doi: 10.1016/j.cie.2018.03.007Ahmadizar, F., Zeynivand, M., Arkat, J. Two-level vehicle routing with cross-docking in a three-echelon supply chain: A genetic algorithm approach (2015) Applied Mathematical Modelling, 39 (22), pp. 7065-7081. Cited 65 times. www.elsevier.com/inca/publications/store/5/2/4/9/9/8/ doi: 10.1016/j.apm.2015.03.005Ai, T.J., Kachitvichyanukul, V. Particle swarm optimization and two solution representations for solving the capacitated vehicle routing problem (2009) Computers and Industrial Engineering, 56 (1), pp. 380-387. Cited 168 times. doi: 10.1016/j.cie.2008.06.012Alamatsaz, K., Ahmadi, A., Mirzapour Al-e-hashem, S.M.J. 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