Mostrar el registro sencillo del ítem

dc.creatorCano J.A.
dc.creatorCorrea-Espinal A.
dc.creatorGómez-Montoya R.
dc.date2020
dc.date.accessioned2021-02-05T14:58:57Z
dc.date.available2021-02-05T14:58:57Z
dc.identifier.issn17558077
dc.identifier.urihttp://hdl.handle.net/11407/6043
dc.descriptionThis article aims to introduce a metaheuristic to solve the order batching problem in multi-parallel-aisle warehouse systems to minimise the travelled distance. The proposed metaheuristic is based on an item-oriented genetic algorithm (GA) using a new chromosome representation where a gen represents a customer order to guarantee feasibility in the mutation operator, decreasing the correction of chromosomes generated by the crossover operator, and avoiding the calculation of the minimum number of feasible batches. When comparing the performance of the proposed algorithm with the first-come-first-served (FCFS) rule in 360 instances, we found average savings of 11% (up to 24%) in travelled distance and 2% (up to 17%) in the number of batches. The proposed algorithm can be easily integrated into a warehouse management system (WMS) to provide significant savings in travelled distances, increasing the efficiency of order-picking operations, and reducing the consumption of energy sources required by picking devices. Copyright © 2020 Inderscience Enterprises Ltd.
dc.language.isoeng
dc.publisherInderscience Publishers
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85094880129&doi=10.1504%2fIJADS.2020.110606&partnerID=40&md5=ee391d71abe2fc4744c8c4638228e256
dc.sourceInternational Journal of Applied Decision Sciences
dc.subjectGenetic algorithmsspa
dc.subjectOrder batchingspa
dc.subjectPicker-to-parts systemsspa
dc.subjectTravelled distancespa
dc.subjectWarehouse managementspa
dc.titleUsing genetic algorithms for order batching in multi-parallel-aisle picker-to-parts systems
dc.typeConference Papereng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programAdministración de Empresasspa
dc.identifier.doi10.1504/IJADS.2020.110606
dc.subject.keywordChromosomeseng
dc.subject.keywordWarehouseseng
dc.subject.keywordConsumption of energyeng
dc.subject.keywordCrossover operatoreng
dc.subject.keywordCustomer orderseng
dc.subject.keywordFirstcome-first-served (FCFS) ruleseng
dc.subject.keywordMutation operatorseng
dc.subject.keywordOrder batchingeng
dc.subject.keywordParallel aisle warehouseeng
dc.subject.keywordWarehouse management systemseng
dc.subject.keywordGenetic algorithmseng
dc.relation.citationvolume13
dc.relation.citationissue4
dc.relation.citationstartpage435
dc.relation.citationendpage447
dc.publisher.facultyFacultad de Ciencias Económicas y Administrativasspa
dc.affiliationCano, J.A., Universidad de Medellín, Carrera 87 # 30-65, Medellín, Colombia
dc.affiliationCorrea-Espinal, A., Universidad Nacional de Colombia, Av. 80 # 65 -, Medellín, 223, Colombia
dc.affiliationGómez-Montoya, R., ESACS - Escuela Superior en Administración de Cadena de Suministro, Calle 4 # 18-55, Medellín, Colombia
dc.relation.referencesAlbareda-Sambola, M., Alonso-Ayuso, A., Molina, E., De Blas, C.S., Variable neighborhood search for order batching in a warehouse (2009) Asia-Pacific Journal of Operational Research, 26 (5), pp. 655-683. , http://doi.org/10.1142/S0217595909002390, [online]
dc.relation.referencesAzadnia, A.H., Taheri, S., Ghadimi, P., Mat Saman, M.Z., Wong, K.Y., Order batching in warehouses by minimizing total tardiness: a hybrid approach of weighted association rule mining and genetic algorithms (2013) The Scientific World Journal, pp. 1-13. , http://doi.org/10.1155/2013/246578, [online]
dc.relation.referencesBoysen, N., Stephan, K., A survey on single crane scheduling in automated storage/retrieval systems (2016) European Journal of Operational Research, 254 (3), pp. 691-704. , http://doi.org/10.1016/j.ejor.2016.04.008, [online]
dc.relation.referencesBoysen, N., de Koster, R., Weidinger, F., Warehousing in the e-commerce era: a survey (2018) European Journal of Operational Research, pp. 1-16. , http://doi.org/10.1016/j.ejor.2018.08.023, [online]
dc.relation.referencesBozer, Y.A., Kile, J.W., Order batching in walk-and-pick order picking systems (2008) International Journal of Production Research, 46 (7), pp. 1887-1909. , http://doi.org/10.1080/00207540600920850, [online]
dc.relation.referencesCano, J.A., Correa-Espinal, A.A., Gómez-Montoya, R.A., An evaluation of picking routing policies to improve warehouse efficiency (2017) International Journal of Industrial Engineering and Management, 8 (4), pp. 229-238. , http://ijiemjournal.uns.ac.rs/previousissues/80-volume-8-2017/volume-8-issue-4/351-an-evaluation-of-picking-routingpolicies-to-improve-warehouse-efficiency, [online] (accessed 26 June 2019)
dc.relation.referencesCano, J.A., Correa-Espinal, A.A., Gómez-Montoya, R.A., A review of research trends in order batching, sequencing and picker routing problems (2018) Espacios, 39 (4), p. 3. , https://www.revistaespacios.com/a18v39n04/18390403.html, [online] (accessed 22 June 2019)
dc.relation.referencesCano, 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) Journal of King Saud University - Engineering Sciences, , http://doi.org/10.1016/J.JKSUES.2019.02.004, [online]
dc.relation.referencesCano, J.A., Correa-Espinal, A.A., Gómez-Montoya, R.A., Cortés, P., Genetic algorithms for the picker routing problem in multi-block warehouses (2019) Lecture Notes in Business Information Processing, 353, pp. 313-322. , http://doi.org/10.1007/978-3-030-20485-3_24, in Abramowicz, W. and Corchuelo, R. (Eds): Springer, Cham [online]
dc.relation.referencesCergibozan, Ç., Tasan, A.S., Order batching operations: an overview of classification, solution techniques, and future research (2016) Journal of Intelligent Manufacturing, pp. 1-15. , http://doi.org/10.1007/s10845-016-1248-4, [online]
dc.relation.referencesChaudhuri, B., Jana, R.K., Sharma, D.K., Dan, P.K., A goal programming embedded genetic algorithm for multi-objective manufacturing cell design (2019) International Journal of Applied Decision Sciences, 12 (1), pp. 98-114. , http://doi.org/10.1504/IJADS.2019.096562, [online]
dc.relation.referencesChen, T.L., Cheng, C.Y., Chen, Y.Y., Chan, L.K., An efficient hybrid algorithm for integrated order batching, sequencing and routing problem (2015) International Journal of Production Economics, 159, pp. 158-167. , http://doi.org/10.1016/j.ijpe.2014.09.029, [online]
dc.relation.referencesChirici, L., Wang, K.S., Tackling the storage problem through genetic algorithms (2014) Advances in Manufacturing, 2 (3), pp. 203-211. , http://doi.org/10.1007/s40436-014-0074-1, [online]
dc.relation.referencesDe Koster, R., Le-Duc, T., Roodbergen, K.J., Design and control of warehouse order picking: a literature review (2007) European Journal of Operational Research, 182 (2), pp. 481-501. , http://doi.org/10.1016/j.ejor.2006.07.009, [online]
dc.relation.referencesDe Koster, R., Van Der Poort, E.S., Wolters, M., Efficient orderbatching methods in warehouses (1999) International Journal of Production Research, 37 (7), pp. 1479-1504. , http://doi.org/10.1080/002075499191094, [online]
dc.relation.referencesDukic, G., Oluic, C., Order-picking methods: improving order-picking efficiency (2007) International Journal of Logistics Systems and Management, 3 (4), pp. 451-460. , http://doi.org/10.1504/IJLSM.2007.013214, [online]
dc.relation.referencesGademann, N., van de Velde, S., Order batching to minimize total travel time in a parallel-aisle warehouse (2005) IIE Transactions, 37 (1), pp. 63-75. , http://doi.org/10.1080/07408170590516917, [online]
dc.relation.referencesGrosse, E.H., Glock, C.H., Neumann, W.P., Human factors in order picking: a content analysis of the literature (2017) International Journal of Production Research, 55 (5), pp. 1260-1276. , http://doi.org/10.1080/00207543.2016.1186296, [online]
dc.relation.referencesHenn, S., Algorithms for on-line order batching in an order picking warehouse (2012) Computers and Operations Research, 39 (11), pp. 2549-2563. , http://doi.org/10.1016/j.cor.2011.12.019, [online]
dc.relation.referencesHenn, S., Schmid, V., Metaheuristics for order batching and sequencing in manual order picking systems (2013) Computers and Industrial Engineering, 66 (2), pp. 338-351. , http://doi.org/10.1016/j.cie.2013.07.003, [online]
dc.relation.referencesHenn, S., Koch, S., Doerner, K.F., Strauss, C., Wäscher, G., Metaheuristics for the order batching problem in manual order picking systems (2010) Business Research, 3 (1), pp. 82-105. , http://doi.org/10.1007/BF03342717, [online]
dc.relation.referencesHsu, C-M., Chen, K-Y., Chen, M-C., Batching orders in warehouses by minimizing travel distance with genetic algorithms (2005) Computers in Industry, 56 (2), pp. 169-178. , http://doi.org/10.1016/j.compind.2004.06.001, [online]
dc.relation.referencesKalyanaraman, P., Keerthika, C., A review on automated storage/retrieval systems and shuttle based storage/retrieval systems (2016) International Journal on Recent and Innovation Trends in Computing and Communication, 4 (11), pp. 167-171
dc.relation.referencesKoch, S., Wäscher, G., A grouping genetic algorithm for the order batching problem in distribution warehouses (2016) Journal of Business Economics, 86 (1), pp. 131-153. , http://doi.org/10.1007/s11573-015-0789-x, [online]
dc.relation.referencesLee, J.A., Chang, Y.S., Shim, H-J., Cho, S-J., A study on the picking process time (2015) 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) and the Affiliated Conferences, AHFE 2015, 3, pp. 731-738. , http://doi.org/10.1016/j.promfg.2015.07.316, Elsevier B.V., Las Vegas, USA [online]
dc.relation.referencesLi, J., Huang, R., Dai, J.B., Joint optimisation of order batching and picker routing in the online retailer's warehouse in China (2017) International Journal of Production Research, 55 (2), pp. 447-461. , http://doi.org/10.1080/00207543.2016.1187313, [online]
dc.relation.referencesLi, Y., Li, Y., E-commerce order batching algorithm based on association rule mining in the era of big data (2018) 2018 Chinese Control And Decision Conference (CCDC), pp. 1934-1939. , http://doi.org/10.1109/CCDC.2018.8407443, [online]
dc.relation.referencesManzini, R., Bozer, Y., Heragu, S., Decision models for the design, optimization and management of warehousing and material handling systems (2015) International Journal of Production Economics, 170 (1), pp. 711-716. , http://doi.org/10.1016/j.ijpe.2015.08.007, [online]
dc.relation.referencesMenéndez, B., Pardo, E.G., Alonso-Ayuso, A., Molina, E., Duarte, A., Variable neighborhood search strategies for the order batching problem (2017) Computers and Operations Research, 78 (1), pp. 500-512. , http://doi.org/10.1016/j.cor.2016.01.020, [online]
dc.relation.referencesMenéndez, B., Pardo, E.G., Sánchez-Oro, J., Duarte, A., Parallel variable neighborhood search for the min-max order batching problem (2017) International Transactions in Operational Research, 24 (3), pp. 635-662. , http://doi.org/10.1111/itor.12309, [online]
dc.relation.referencesMontoya-Torres, J.R., Aponte, A., Rosas, P., Caballero-Villalobos, J.P., Applying GRASP meta-heuristic to solve the single-item two-echelon uncapacitated facility location problem (2010) International Journal of Applied Decision Sciences, 3 (4), pp. 297-310. , http://doi.org/10.1504/IJADS.2010.036849, [online]
dc.relation.referencesMu, S., Task scheduling optimisation algorithm based on load balance under the cloud computing environment (2018) International Journal of Applied Decision Sciences, 11 (2), pp. 210-222. , http://doi.org/10.1504/IJADS.2018.090932, [online]
dc.relation.referencesÖncan, T., A genetic algorithm for the order batching problem in low-level picker-to-part warehouse systems (2013) Lecture Notes in Engineering and Computer Science, 2202, pp. 19-24. , http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp19-24.pdf, Newswood Limited, Kowloon [online] (accessed 22 June 2019)
dc.relation.referencesÖztürko, Ö., Discrete optimization a discrete cross aisle design model for order-picking warehouses (2019) European Journal of Operational Research, 275, pp. 411-430. , http://doi.org/10.1016/j.ejor.2018.11.037, [online]
dc.relation.referencesPan, J.C-H., Shih, P-H., Wu, M-H., Order batching in a pick-and-pass warehousing system with group genetic algorithm (2015) Omega, 57 (B), pp. 238-248. , http://doi.org/10.1016/j.omega.2015.05.004, [online]
dc.relation.referencesPérez-Rodríguez, R., Hernández-Aguirre, A., An estimation of distribution algorithm based approach for the order batching problem (2015) Research in Computing Science, 93 (1), pp. 141-150
dc.relation.referencesPrasse, C., Nettstraeter, A., Ten Hompel, M., How IoT will change the design and operation of logistics systems (2014) 2014 International Conference on the Internet of Things, IOT, pp. 55-60. , http://doi.org/10.1109/IOT.2014.7030115, [online]
dc.relation.referencesRubrico, J.I.U., Ota, J., Higashi, T., Tamura, H., Metaheuristic scheduling of multiple picking agents for warehouse management (2008) Industrial Robot: An International Journal, 35 (1), pp. 58-68. , http://doi.org/http://dx.doi.org/10.1108/01439910810843298, [online]
dc.relation.referencesScholz, A., Wäscher, G., Order batching and picker routing in manual order picking systems: the benefits of integrated routing (2017) Central European Journal of Operations Research, 25 (2), pp. 491-520. , http://doi.org/10.1007/s10100-017-0467-x, [online]
dc.relation.referencesSun, M., Pang, D., Vehicle routing optimisation algorithm for agricultural products logistics distribution (2017) International Journal of Applied Decision Sciences, 10 (4), pp. 327-334. , http://doi.org/10.1504/IJADS.2017.087175, [online]
dc.relation.referencesTappia, E., Roy, D., de Koster, R., Melacini, M., Modeling, analysis, and design insights for shuttle-based compact storage systems (2017) Transportation Science, 51 (1), pp. 1-28. , http://doi.org/10.1287/trsc.2016.0699, [online]
dc.relation.referencesTejesh, B.S.S., Neeraja, S., Warehouse inventory management system using IoT and open source framework (2018) Alexandria Engineering Journal, 57 (4), pp. 3817-3823. , http://doi.org/10.1016/j.aej.2018.02.003, [online]
dc.relation.referencesTompkins, J.A., White, J.A., Bozer, Y.A., Tanchoco, J.M.A., (2010) Facilities Planning, , https://es.scribd.com/doc/249331171/Facilities-Planning-Tompkins-A-White-A-Bozer-Tanchoco-4ed-Solution-Manual, 4th ed., Wiley, New Jersey [online] (accessed 18 May 2019)
dc.relation.referencesTosun, O., Aktan, H.E., A multi criteria decision-making approach to evaluate automated storage and retrieval systems (2016) International Journal of Applied Decision Sciences, 9 (2), pp. 182-195. , http://doi.org/10.1504/IJADS.2016.080122, [online]
dc.relation.referencesTrab, S., Bajic, E., Zouinkhi, A., Abdelkrim, M.N., Chekir, H., Ltaief, R.H., Product allocation planning with safety compatibility constraints in IoT-based warehouse (2015) Procedia Computer Science, 73, pp. 290-297. , http://doi.org/10.1016/j.procs.2015.12.033, [online]
dc.relation.referencesTsai, C-Y., Liou, J.J.H., Huang, T-M., Using a multiple-GA method to solve the batch picking problem: considering travel distance and order due time (2008) International Journal of Production Research, 46 (22), pp. 6533-6555. , http://doi.org/10.1080/00207540701441947, [online]
dc.relation.referencesVan Gils, T., Caris, A., Ramaekers, K., Braekers, K., de Koster, R.B.M., Designing efficient order picking systems: the effect of real-life features on the relationship among planning problems (2019) Transportation Research Part E, 125, pp. 47-73. , http://doi.org/10.1016/j.tre.2019.02.010, [online]
dc.relation.referencesVan 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) European Journal of Operational Research, 267 (1), pp. 1-15. , http://doi.org/10.1016/j.ejor.2017.09.002, [online]
dc.relation.referencesWen, L., Bai, L., Systematic layout planning and comprehensive evaluation in manufacture enterprise's logistics facilities (2015) International Journal of Applied Decision Sciences, 8 (4), pp. 358-375. , http://doi.org/10.1504/IJADS.2015.074620, [online]
dc.relation.referencesYener, F., Yazgan, H.R., Optimal warehouse design: literature review and case study application (2019) Computers & Industrial Engineering, 129, pp. 1-13. , http://doi.org/10.1016/j.cie.2019.01.006, [online]
dc.relation.referencesZhang, J., Wang, X., Chan, F.T.S., Ruan, J., On-line order batching and sequencing problem with multiple pickers: a hybrid rule-based algorithm (2017) Applied Mathematical Modelling, 45 (1), pp. 271-284. , http://doi.org/10.1016/j.apm.2016.12.012, [online]
dc.relation.referencesZhang, R., Wang, M., Pan, X., Computers & industrial engineering new model of the storage location assignment problem considering demand correlation pattern (2019) Computers & Industrial Engineering, 129, pp. 210-219. , http://doi.org/10.1016/j.cie.2019.01.027, [online]
dc.relation.referencesZhu, J., Zhang, H., Zhou, L., Guo, J., Order batching optimization in dual zone type warehouse (2015) Science Journal of Business and Management, 3 (3), pp. 77-81. , http://doi.org/10.11648/j.ijebo.20150303.13., [online]
dc.relation.referencesZulj, I., Kramer, S., Schneider, M., A hybrid of adaptive large neighborhood search and tabu search for the order-batching problem (2018) European Journal of Operational Research, 264 (2), pp. 653-664. , http://doi.org/10.1016/j.ejor.2017.06.056, [online]
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.driverinfo:eu-repo/semantics/other


Ficheros en el ítem

FicherosTamañoFormatoVer

No hay ficheros asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem