dc.contributor.author | Cano J.A | |
dc.contributor.author | Cortés P | |
dc.contributor.author | Campo E.A | |
dc.contributor.author | Correa-Espinal A.A. | |
dc.date.accessioned | 2022-09-14T14:33:55Z | |
dc.date.available | 2022-09-14T14:33:55Z | |
dc.date.created | 2021 | |
dc.identifier.issn | 17509653 | |
dc.identifier.uri | http://hdl.handle.net/11407/7519 | |
dc.description | This article solves the order batching, batch assignment, and sequencing problem (JOBASP) given multiple objectives and heterogeneous picking vehicles in multi-parallel-aisle warehouse systems. A multi-objective grouping genetic algorithm (GGA) is developed to minimize total travel time and total tardiness by implementing an encoding scheme where a gene represents orders grouped in a batch and the assignment of the batch to a picking vehicle. Computer simulations show that the proposed algorithm performs 25.4% better than a first come, first served (FCFS) rule–based heuristic and 10.2% better than an earliest due date (EDD) rule–based heuristic. The proposed GGA provides significant savings of up to 46.8% and 28.4% on travel time and tardiness, respectively, for these benchmark heuristics. Therefore, this article introduces a GGA to solve the JOBASP with a reasonable computing time, making this approach interesting for warehouse operators using heterogeneous picking vehicles and addressing multiple objectives. © 2021 International Society of Management Science and Engineering Management. | eng |
dc.language.iso | eng | |
dc.publisher | Taylor and Francis Ltd. | |
dc.relation.isversionof | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118711477&doi=10.1080%2f17509653.2021.1991852&partnerID=40&md5=99460c6c6d9fc9623edf1f082208077c | |
dc.source | International Journal of Management Science and Engineering Management | |
dc.title | MULTI-OBJECTIVE GROUPING GENETIC ALGORITHM FOR THE JOINT ORDER BATCHING, BATCH ASSIGNMENT, AND SEQUENCING PROBLEM | |
dc.type | Article | |
dc.rights.accessrights | info:eu-repo/semantics/restrictedAccess | |
dc.publisher.program | Administración de Empresas | |
dc.type.spa | Artículo | |
dc.identifier.doi | 10.1080/17509653.2021.1991852 | |
dc.subject.keyword | Batch assignment | eng |
dc.subject.keyword | Grouping genetic algorithms | eng |
dc.subject.keyword | Joint order picking | eng |
dc.subject.keyword | Multi-objective problem | eng |
dc.subject.keyword | Order batching | eng |
dc.subject.keyword | Order picking | eng |
dc.subject.keyword | Sequencing | eng |
dc.publisher.faculty | Facultad de Ciencias Económicas y Administrativas | |
dc.affiliation | Cano, J.A., Faculty of Economic and Administrative Sciences, Universidad de Medellín, Medellín, Colombia | |
dc.affiliation | Cortés, P., Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, Sevilla, Spain | |
dc.affiliation | Campo, E.A., Politécnico Colombiano Jaime Isaza Cadavid, Medellín, Colombia | |
dc.affiliation | Correa-Espinal, A.A., Facultad de Minas, Universidad Nacional de Colombia, Medellín, Colombia | |
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dc.type.coar | http://purl.org/coar/resource_type/c_6501 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | |
dc.type.driver | info:eu-repo/semantics/article | |
dc.identifier.reponame | reponame:Repositorio Institucional Universidad de Medellín | |
dc.identifier.repourl | repourl:https://repository.udem.edu.co/ | |
dc.identifier.instname | instname:Universidad de Medellín | |