Multi-population genetic algorithm to solve the synchronized and integrated two-level lot sizing and scheduling problem
dc.contributor.author | Toledo, C. F. M. | |
dc.contributor.author | Franca, P. M. [UNESP] | |
dc.contributor.author | Morabito, R. | |
dc.contributor.author | Kimms, A. | |
dc.contributor.institution | Univ Duisburg Essen | |
dc.contributor.institution | Universidade Federal de Lavras (UFLA) | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.contributor.institution | Universidade Federal de São Carlos (UFSCar) | |
dc.date.accessioned | 2014-05-20T13:23:33Z | |
dc.date.available | 2014-05-20T13:23:33Z | |
dc.date.issued | 2009-01-01 | |
dc.description.abstract | This paper introduces an evolutionary algorithm as a procedure to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem (SITLSP). This problem can be found in some industrial settings, mainly soft drink companies, where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot-sizing and scheduling of raw materials in tanks and soft drinks in bottling lines, where setup costs and times depend on the previous items stored and bottled. A multi-population genetic algorithm approach with a novel representation of solutions for individuals and a hierarchical ternary tree structure for populations is proposed. Computational tests include comparisons with an exact approach for small-to-moderate-sized instances and with real-world production plans provided by a manufacturer. | en |
dc.description.affiliation | Univ Duisburg Essen, Dept Technol & Operat Management, D-47048 Duisburg, Germany | |
dc.description.affiliation | Universidade Federal de Lavras (UFLA), Dept Ciência Computacao, BR-37200000 Lavras, MG, Brazil | |
dc.description.affiliation | Univ Estadual Paulista, Dept Matemat Estat & Computacao, Fac Ciencias & Tecnol, BR-19060900 Presidente Prudente, SP, Brazil | |
dc.description.affiliation | Universidade Federal de São Carlos (UFSCar), Dept Engn Producao, BR-13565905 São Carlos, SP, Brazil | |
dc.description.affiliationUnesp | Univ Estadual Paulista, Dept Matemat Estat & Computacao, Fac Ciencias & Tecnol, BR-19060900 Presidente Prudente, SP, Brazil | |
dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
dc.description.sponsorshipId | FAPESP: 00/02609-2 | |
dc.description.sponsorshipId | CNPq: 303956/2003-8 | |
dc.description.sponsorshipId | CNPq: 522973/95-7 | |
dc.format.extent | 3097-3119 | |
dc.identifier | http://dx.doi.org/10.1080/00207540701675833 | |
dc.identifier.citation | International Journal of Production Research. Abingdon: Taylor & Francis Ltd, v. 47, n. 11, p. 3097-3119, 2009. | |
dc.identifier.doi | 10.1080/00207540701675833 | |
dc.identifier.issn | 0020-7543 | |
dc.identifier.uri | http://hdl.handle.net/11449/7117 | |
dc.identifier.wos | WOS:000265289100014 | |
dc.language.iso | eng | |
dc.publisher | Taylor & Francis Ltd | |
dc.relation.ispartof | International Journal of Production Research | |
dc.relation.ispartofjcr | 2.623 | |
dc.relation.ispartofsjr | 1,432 | |
dc.rights.accessRights | Acesso restrito | |
dc.source | Web of Science | |
dc.subject | lot-sizing and scheduling | en |
dc.subject | production planning | en |
dc.subject | combinatorial optimization | en |
dc.subject | genetic algorithm | en |
dc.subject | soft drink manufacturing | en |
dc.title | Multi-population genetic algorithm to solve the synchronized and integrated two-level lot sizing and scheduling problem | en |
dc.type | Artigo | |
dcterms.license | http://journalauthors.tandf.co.uk/permissions/reusingOwnWork.asp | |
dcterms.rightsHolder | Taylor & Francis Ltd | |
unesp.campus | Universidade Estadual Paulista (Unesp), Faculdade de Ciências e Tecnologia, Presidente Prudente | pt |
unesp.department | Matemática e Computação - FCT | pt |
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