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

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 sol...

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Fecha de publicación:
2020
Institución:
Universidad de Medellín
Repositorio:
Repositorio UDEM
Idioma:
eng
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oai:repository.udem.edu.co:11407/5907
Acceso en línea:
http://hdl.handle.net/11407/5907
Palabra clave:
Discrete particle swarm optimization
Distribution centre
Order picking
Put-away routing
Warehouse management
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id REPOUDEM2_2133b73702523cbdaae5d53c403a98cb
oai_identifier_str oai:repository.udem.edu.co:11407/5907
network_acronym_str REPOUDEM2
network_name_str Repositorio UDEM
repository_id_str
dc.title.none.fl_str_mv A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
spellingShingle A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
Discrete particle swarm optimization
Distribution centre
Order picking
Put-away routing
Warehouse management
title_short A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title_full A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title_fullStr A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title_full_unstemmed A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
title_sort A discrete particle swarm optimization to solve the put-away routing problem in distribution centres
dc.subject.spa.fl_str_mv Discrete particle swarm optimization
Distribution centre
Order picking
Put-away routing
Warehouse management
topic Discrete particle swarm optimization
Distribution centre
Order picking
Put-away routing
Warehouse management
description 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.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2021-02-05T14:57:46Z
dc.date.available.none.fl_str_mv 2021-02-05T14:57:46Z
dc.date.none.fl_str_mv 2020
dc.type.eng.fl_str_mv Article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
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http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/article
dc.identifier.issn.none.fl_str_mv 20793197
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/11407/5907
dc.identifier.doi.none.fl_str_mv 10.3390/computation8040099
identifier_str_mv 20793197
10.3390/computation8040099
url http://hdl.handle.net/11407/5907
dc.language.iso.none.fl_str_mv eng
language eng
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dc.relation.citationissue.none.fl_str_mv 4
dc.relation.citationstartpage.none.fl_str_mv 1
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dc.relation.references.none.fl_str_mv Bartholdi, J.J., Hackman, S.T., (2014) Warehouse & Distribution Science, , The Supply Chain and Logistics Institute: Atlanta, GA, USA
CSCMP Supply Chain Management: Terms and Glossary, , https://bit.ly/2e3NMGE, (accessed on 8 November 2016)
Cano, J.A., Correa-Espinal, A., Gómez-Montoya, R.A., Solving the Order Batching Problem in Warehouses using Genetic Algorithms (2018) Inf. Tecnol, 29, pp. 235-244. , [CrossRef]
Cano, J.A., Order Picking Optimization Based on a Picker Routing Heuristic: Minimizing Total Traveled Distance in Warehouses (2020) Handbook of Research on the Applications of International Transportation and Logistics for World Trade, pp. 74-96. , Ceyhun, G.Ç., Ed.
IGI Global: Hershey, PA, USA
Van Gils, T., Ramaekers, K., Caris, A., de Koster, R.B.M., Designing Efficient Order Picking Systems by Combining Planning Problems: State-of-the-art Classification and Review (2018) Eur. J. Oper. Res, 267, pp. 1-15. , [CrossRef]
Cano, J.A., Formulations for joint order picking problems in low-level picker-to-part systems (2020) Bull. Electr. Eng. Inform, 9, pp. 836-844. , [CrossRef]
Yan, H., Tang, S.-L., Pre-distribution and post-distribution cross-docking operations (2009) Transp. Res. Part E Logist. Transp. Rev, 45, pp. 843-859. , [CrossRef]
De Koster, R., Le-Duc, T., Roodbergen, K.J., Design and control of warehouse order picking: A literature review (2007) Eur. J. Oper. Res, 182, pp. 481-501. , [CrossRef]
Buijs, P., Danhof, H.W., Wortmann, J.H.C., Just-in-Time Retail Distribution: A Systems Perspective on Cross-Docking (2016) J. Bus. Logist, 37, pp. 213-230. , [CrossRef]
Frazelle, E.H., (2016) World-Class Warehousing and Material Handling, , 2nd ed.
McGraw-Hill Education: New York, NY, USA, ISBN 9780071842822
Gómez, R.A., Correa, A., Muñuzuri, J., Cortes, P., Comparative analysis of order batching and routing problem in the picking regarding classical HVRP (heterogeneous vehicle routing problem) [Análisis comparativo del problema de conformación de lotes con ruteo en la preparación de pedidos respecto al HVRP] (2016) Dir. Organ, 59, pp. 49-60
Chan, F.T.S., Chan, H.K., Improving the productivity of order picking of a manual-pick and multi-level rack distribution warehouse through the implementation of class-based storage (2011) Expert Syst. Appl, 38, pp. 2686-2700. , [CrossRef]
Muppani, V.R., Adil, G.K., Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach (2008) Omega, 36, pp. 609-618. , [CrossRef]
Kim, B.S., Smith, J.S., Slotting methodology using correlated improvement for a zone-based carton picking distribution system (2012) Comput. Ind. Eng, 62, pp. 286-295. , [CrossRef]
Takahama, H., Nishi, T., Konishi, M., Imai, J., A determination method of product allocation schedule for warehouse management Proceedings of the 41st SICE Annual Conference, SICE 2002, pp. 1004-1007. , Osaka, Japan, 5–7 August 2002
Heragu, S.S., Du, L., Mantel, R.J., Schuur, P.C., Mathematical model for warehouse design and product allocation (2005) Int. J. Prod. Res, 43, pp. 327-350. , [CrossRef]
Hou, J.L., Wu, Y.J., Yang, Y.J., A model for storage arrangement and re-allocation for storage management operations (2010) Int. J. Comput. Integr. Manuf, 23, pp. 369-390. , [CrossRef]
Kutzelnigg, R., Optimal allocation of goods in a warehouse: Minimizing the order picking costs under real-life constraints Proceedings of the LINDI 2011—3rd IEEE International Symposium on Logistics and Industrial Informatics, pp. 65-70. , Budapest, Hungary, 25–27 August 2011
Gómez, R.A., Giraldo, O.G., Campo, E.A., Conformación de Lotes Mínimo Tiempo en la Operación de Acomodo Considerando k Equipos Homogéneos usando Metaheurísticos (2016) Inf. Tecnol, 27, pp. 53-62. , [CrossRef]
Correa, A., Rodríguez, E., Gómez, R., Modelamiento del ruteo del acomodo de tiempo mínimo en centros de distribución (CEDI) usando búsqueda tabú (2014) Rev. Soluc. Postgrado EIA, 6, pp. 15-28
Bai, Q., Analysis of particle swarm optimization algorithm (2010) Comput. Inf. Sci, 3, pp. 180-184. , [CrossRef]
Goksal, F., Karaoglan, I., Altiparmak, F., A Hybrid Discrete Particle Swarm Optimization for Vehicle Routing Problem with Simultaneous Pickup and Delivery (2013) Comput. Ind. Eng, 65, pp. 39-53. , [CrossRef]
Chen, F., Wang, H., Xie, Y., Qi, C., An ACO-based online routing method for multiple order pickers with congestion consideration in warehouse (2016) J. Intell. Manuf, 27, pp. 389-408. , [CrossRef]
Masae, M., Glock, C.H., Grosse, E.H., Order picker routing in warehouses: A systematic literature review (2020) Int. J. Prod. Econ, 224, p. 107564. , [CrossRef]
Chen, A.L., Yang, G.K., Wu, Z.M., Hybrid Discrete Particle Swarm Optimization Algorithm for Capacitated Vehicle Routing Problem (2006) J. Zhejiang Univ. Sci. A, 7, pp. 607-614. , [CrossRef]
Gong, Y.J., Zhang, J., Liu, O., Huang, R.Z., Chung, H.S.H., Shi, Y.H., Optimizing the Vehicle Routing Problem with Time Windows: A Discrete Particle Swarm Optimization Approach (2011) IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.), 42, pp. 254-267. , [CrossRef]
Wu, D., Dong, M., Li, M., Li, F., Vehicle routing problem with time windows using multi-objective co-evolutionary approach (2016) Int. J. Simul. Model, 15, pp. 742-753. , [CrossRef]
Alinaghian, M., Ghazanfari, M., Norouzi, N., Nouralizadeh, H., A Novel Model for the Time Dependent Competitive Vehicle Routing Problem: Modified Random Topology Particle Swarm Optimization (2017) Netw. Spat. Econ, 17, pp. 1185-1211. , [CrossRef]
Zhu, L., Hu, D., Study on the vehicle routing problem considering congestion and emission factors (2019) Int. J. Prod. Res, 57, pp. 6115-6129. , [CrossRef]
Harbaoui Dridi, I., Ben Alaïa, E., Borne, P., Bouchriha, H., Optimisation of the multi-depots pick-up and delivery problems with time windows and multi-vehicles using PSO algorithm (2020) Int. J. Prod. Res, 58, pp. 4201-4214. , [CrossRef]
Tebaldi, L., Bigliardi, B., Bottani, E., Sustainable supply chain and innovation: A review of the recent literature (2018) Sustainability, 10, p. 3946. , [CrossRef]
Di Nardo, M., Clericuzio, M., Murino, T., Sepe, C., An economic order quantity stochastic dynamic optimization model in a logistic 4.0 environment (2020) Sustainability, 12, p. 4075. , [CrossRef]
Di Nardo, M., Forino, D., Murino, T., The evolution of man–machine interaction: The role of human in Industry 4.0 paradigm (2020) Prod. Manuf. Res, 8, pp. 20-34. , [CrossRef]
Lu, W., McFarlane, D., Giannikas, V., Zhang, Q., An algorithm for dynamic order-picking in warehouse operations (2016) Eur. J. Oper. Res, 248, pp. 107-122. , [CrossRef]
Schrotenboer, A.H., Wruck, S., Roodbergen, K.J., Veenstra, M., Dijkstra, A.S., Order picker routing with product returns and interaction delays (2017) Int. J. Prod. Res, 55, pp. 6394-6406. , [CrossRef]
Cano, J.A., Correa-Espinal, A.A., Gómez-Montoya, R.A., Mathematical programming modeling for joint order batching, sequencing and picker routing problems in manual order picking systems (2019) J. King Saud Univ. Eng. Sci, 32, pp. 219-228. , [CrossRef]
De Vries, J., de Koster, R., Stam, D., Exploring the Role of Picker Personality in Predicting Picking Performance with Pick by Voice, Pick to Light and RF-Terminal Picking (2015) Int. J. Prod. Res, 54, pp. 2260-2274. , [CrossRef]
Kennedy, J., Eberhart, R.C., A discrete binary version of the particle swarm algorithm (1997) Proceedings of the IEEE International Conference on Computational Cybernetics and Simulation, pp. 4104-4108. , Orlando, FL, USA, 12–15 October
Lin, M.Y., Chin, K.S., Tsui, K.L., Wong, T.C., Genetic based discrete particle swarm optimization for Elderly Day Care Center timetabling (2016) Comput. Oper. Res, 65, pp. 125-138. , [CrossRef]
Cortés, P., Gómez-Montoya, R.A., Muñuzuri, J., Correa-Espinal, A., A tabu search approach to solving the picking routing problem for large-and medium-size distribution centres considering the availability of inventory and K heterogeneous material handling equipment (2017) Appl. Soft Comput, 53, pp. 61-73. , [CrossRef]
Henn, S., Algorithms for on-line order batching in an order picking warehouse (2012) Comput. Oper. Res, 39, pp. 2549-2563. , [CrossRef]
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
rights_invalid_str_mv http://purl.org/coar/access_right/c_16ec
dc.publisher.none.fl_str_mv MDPI AG
dc.publisher.program.spa.fl_str_mv Administración de Empresas
dc.publisher.faculty.spa.fl_str_mv Facultad de Ciencias Económicas y Administrativas
publisher.none.fl_str_mv MDPI AG
dc.source.none.fl_str_mv Computation
institution Universidad de Medellín
repository.name.fl_str_mv Repositorio Institucional Universidad de Medellin
repository.mail.fl_str_mv repositorio@udem.edu.co
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spelling 20202021-02-05T14:57:46Z2021-02-05T14:57:46Z20793197http://hdl.handle.net/11407/590710.3390/computation8040099Put-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.engMDPI AGAdministración de EmpresasFacultad de Ciencias Económicas y Administrativashttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85097316780&doi=10.3390%2fcomputation8040099&partnerID=40&md5=29b5f681fe2dd8a5243b74c4dd26613a84117Bartholdi, J.J., Hackman, S.T., (2014) Warehouse & Distribution Science, , The Supply Chain and Logistics Institute: Atlanta, GA, USACSCMP Supply Chain Management: Terms and Glossary, , https://bit.ly/2e3NMGE, (accessed on 8 November 2016)Cano, J.A., Correa-Espinal, A., Gómez-Montoya, R.A., Solving the Order Batching Problem in Warehouses using Genetic Algorithms (2018) Inf. Tecnol, 29, pp. 235-244. , [CrossRef]Cano, J.A., Order Picking Optimization Based on a Picker Routing Heuristic: Minimizing Total Traveled Distance in Warehouses (2020) Handbook of Research on the Applications of International Transportation and Logistics for World Trade, pp. 74-96. , Ceyhun, G.Ç., Ed.IGI Global: Hershey, PA, USAVan Gils, T., Ramaekers, K., Caris, A., de Koster, R.B.M., Designing Efficient Order Picking Systems by Combining Planning Problems: State-of-the-art Classification and Review (2018) Eur. J. Oper. Res, 267, pp. 1-15. , [CrossRef]Cano, J.A., Formulations for joint order picking problems in low-level picker-to-part systems (2020) Bull. Electr. Eng. Inform, 9, pp. 836-844. , [CrossRef]Yan, H., Tang, S.-L., Pre-distribution and post-distribution cross-docking operations (2009) Transp. Res. Part E Logist. Transp. Rev, 45, pp. 843-859. , [CrossRef]De Koster, R., Le-Duc, T., Roodbergen, K.J., Design and control of warehouse order picking: A literature review (2007) Eur. J. Oper. Res, 182, pp. 481-501. , [CrossRef]Buijs, P., Danhof, H.W., Wortmann, J.H.C., Just-in-Time Retail Distribution: A Systems Perspective on Cross-Docking (2016) J. Bus. Logist, 37, pp. 213-230. , [CrossRef]Frazelle, E.H., (2016) World-Class Warehousing and Material Handling, , 2nd ed.McGraw-Hill Education: New York, NY, USA, ISBN 9780071842822Gómez, R.A., Correa, A., Muñuzuri, J., Cortes, P., Comparative analysis of order batching and routing problem in the picking regarding classical HVRP (heterogeneous vehicle routing problem) [Análisis comparativo del problema de conformación de lotes con ruteo en la preparación de pedidos respecto al HVRP] (2016) Dir. Organ, 59, pp. 49-60Chan, F.T.S., Chan, H.K., Improving the productivity of order picking of a manual-pick and multi-level rack distribution warehouse through the implementation of class-based storage (2011) Expert Syst. Appl, 38, pp. 2686-2700. , [CrossRef]Muppani, V.R., Adil, G.K., Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach (2008) Omega, 36, pp. 609-618. , [CrossRef]Kim, B.S., Smith, J.S., Slotting methodology using correlated improvement for a zone-based carton picking distribution system (2012) Comput. Ind. Eng, 62, pp. 286-295. , [CrossRef]Takahama, H., Nishi, T., Konishi, M., Imai, J., A determination method of product allocation schedule for warehouse management Proceedings of the 41st SICE Annual Conference, SICE 2002, pp. 1004-1007. , Osaka, Japan, 5–7 August 2002Heragu, S.S., Du, L., Mantel, R.J., Schuur, P.C., Mathematical model for warehouse design and product allocation (2005) Int. J. Prod. Res, 43, pp. 327-350. , [CrossRef]Hou, J.L., Wu, Y.J., Yang, Y.J., A model for storage arrangement and re-allocation for storage management operations (2010) Int. J. Comput. Integr. Manuf, 23, pp. 369-390. , [CrossRef]Kutzelnigg, R., Optimal allocation of goods in a warehouse: Minimizing the order picking costs under real-life constraints Proceedings of the LINDI 2011—3rd IEEE International Symposium on Logistics and Industrial Informatics, pp. 65-70. , Budapest, Hungary, 25–27 August 2011Gómez, R.A., Giraldo, O.G., Campo, E.A., Conformación de Lotes Mínimo Tiempo en la Operación de Acomodo Considerando k Equipos Homogéneos usando Metaheurísticos (2016) Inf. Tecnol, 27, pp. 53-62. , [CrossRef]Correa, A., Rodríguez, E., Gómez, R., Modelamiento del ruteo del acomodo de tiempo mínimo en centros de distribución (CEDI) usando búsqueda tabú (2014) Rev. Soluc. Postgrado EIA, 6, pp. 15-28Bai, Q., Analysis of particle swarm optimization algorithm (2010) Comput. Inf. Sci, 3, pp. 180-184. , [CrossRef]Goksal, F., Karaoglan, I., Altiparmak, F., A Hybrid Discrete Particle Swarm Optimization for Vehicle Routing Problem with Simultaneous Pickup and Delivery (2013) Comput. Ind. Eng, 65, pp. 39-53. , [CrossRef]Chen, F., Wang, H., Xie, Y., Qi, C., An ACO-based online routing method for multiple order pickers with congestion consideration in warehouse (2016) J. Intell. Manuf, 27, pp. 389-408. , [CrossRef]Masae, M., Glock, C.H., Grosse, E.H., Order picker routing in warehouses: A systematic literature review (2020) Int. J. Prod. Econ, 224, p. 107564. , [CrossRef]Chen, A.L., Yang, G.K., Wu, Z.M., Hybrid Discrete Particle Swarm Optimization Algorithm for Capacitated Vehicle Routing Problem (2006) J. Zhejiang Univ. Sci. A, 7, pp. 607-614. , [CrossRef]Gong, Y.J., Zhang, J., Liu, O., Huang, R.Z., Chung, H.S.H., Shi, Y.H., Optimizing the Vehicle Routing Problem with Time Windows: A Discrete Particle Swarm Optimization Approach (2011) IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.), 42, pp. 254-267. , [CrossRef]Wu, D., Dong, M., Li, M., Li, F., Vehicle routing problem with time windows using multi-objective co-evolutionary approach (2016) Int. J. Simul. Model, 15, pp. 742-753. , [CrossRef]Alinaghian, M., Ghazanfari, M., Norouzi, N., Nouralizadeh, H., A Novel Model for the Time Dependent Competitive Vehicle Routing Problem: Modified Random Topology Particle Swarm Optimization (2017) Netw. Spat. Econ, 17, pp. 1185-1211. , [CrossRef]Zhu, L., Hu, D., Study on the vehicle routing problem considering congestion and emission factors (2019) Int. J. Prod. Res, 57, pp. 6115-6129. , [CrossRef]Harbaoui Dridi, I., Ben Alaïa, E., Borne, P., Bouchriha, H., Optimisation of the multi-depots pick-up and delivery problems with time windows and multi-vehicles using PSO algorithm (2020) Int. J. Prod. Res, 58, pp. 4201-4214. , [CrossRef]Tebaldi, L., Bigliardi, B., Bottani, E., Sustainable supply chain and innovation: A review of the recent literature (2018) Sustainability, 10, p. 3946. , [CrossRef]Di Nardo, M., Clericuzio, M., Murino, T., Sepe, C., An economic order quantity stochastic dynamic optimization model in a logistic 4.0 environment (2020) Sustainability, 12, p. 4075. , [CrossRef]Di Nardo, M., Forino, D., Murino, T., The evolution of man–machine interaction: The role of human in Industry 4.0 paradigm (2020) Prod. Manuf. Res, 8, pp. 20-34. , [CrossRef]Lu, W., McFarlane, D., Giannikas, V., Zhang, Q., An algorithm for dynamic order-picking in warehouse operations (2016) Eur. J. Oper. Res, 248, pp. 107-122. , [CrossRef]Schrotenboer, A.H., Wruck, S., Roodbergen, K.J., Veenstra, M., Dijkstra, A.S., Order picker routing with product returns and interaction delays (2017) Int. J. Prod. Res, 55, pp. 6394-6406. , [CrossRef]Cano, J.A., Correa-Espinal, A.A., Gómez-Montoya, R.A., Mathematical programming modeling for joint order batching, sequencing and picker routing problems in manual order picking systems (2019) J. King Saud Univ. Eng. Sci, 32, pp. 219-228. , [CrossRef]De Vries, J., de Koster, R., Stam, D., Exploring the Role of Picker Personality in Predicting Picking Performance with Pick by Voice, Pick to Light and RF-Terminal Picking (2015) Int. J. Prod. Res, 54, pp. 2260-2274. , [CrossRef]Kennedy, J., Eberhart, R.C., A discrete binary version of the particle swarm algorithm (1997) Proceedings of the IEEE International Conference on Computational Cybernetics and Simulation, pp. 4104-4108. , Orlando, FL, USA, 12–15 OctoberLin, M.Y., Chin, K.S., Tsui, K.L., Wong, T.C., Genetic based discrete particle swarm optimization for Elderly Day Care Center timetabling (2016) Comput. Oper. Res, 65, pp. 125-138. , [CrossRef]Cortés, P., Gómez-Montoya, R.A., Muñuzuri, J., Correa-Espinal, A., A tabu search approach to solving the picking routing problem for large-and medium-size distribution centres considering the availability of inventory and K heterogeneous material handling equipment (2017) Appl. Soft Comput, 53, pp. 61-73. , [CrossRef]Henn, S., Algorithms for on-line order batching in an order picking warehouse (2012) Comput. Oper. Res, 39, pp. 2549-2563. , [CrossRef]ComputationDiscrete particle swarm optimizationDistribution centreOrder pickingPut-away routingWarehouse managementA discrete particle swarm optimization to solve the put-away routing problem in distribution centresArticleinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Gómez-Montoya, R.A., Facultad de Administración, Politécnico Colombiano Jaime Isaza Cadavid, Carrera 48 No. 7–151, Medellín, 050022, Colombia, ESACS–Escuela Superior en Administración de Cadena de Suministro, Calle 4 # 18-55, Medellín, 050021, ColombiaCano, J.A., Facultad de Ciencias Económicas y Administrativas, Universidad de Medellín, Carrera 87 # 30–65, Medellín, 050026, ColombiaCortés, P., Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, Camino de los Descubrimientos s/n, Sevilla, 41092, SpainSalazar, F., Facultad de Ciencias Económicas y Administrativas, Pontificia Universidad Javeriana, Cra. 7 #40, Bogotá, 110231, Colombiahttp://purl.org/coar/access_right/c_16ecGómez-Montoya R.A.Cano J.A.Cortés P.Salazar F.11407/5907oai:repository.udem.edu.co:11407/59072021-02-05 09:57:46.136Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co

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