A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorMotta Toledo, Claudio Fabiano
dc.creatorOliveira, Lucas de
dc.creatorPereira, Rodrigo de Freitas
dc.creatorFranca, Paulo Morelato
dc.creatorMorabito, Reinaldo
dc.date2014-12-03T13:11:40Z
dc.date2016-10-25T20:14:48Z
dc.date2014-12-03T13:11:40Z
dc.date2016-10-25T20:14:48Z
dc.date2014-08-01
dc.date.accessioned2017-04-06T06:33:08Z
dc.date.available2017-04-06T06:33:08Z
dc.identifierComputers & Operations Research. Oxford: Pergamon-elsevier Science Ltd, v. 48, p. 40-52, 2014.
dc.identifier0305-0548
dc.identifierhttp://hdl.handle.net/11449/113404
dc.identifierhttp://acervodigital.unesp.br/handle/11449/113404
dc.identifier10.1016/j.cor.2014.02.012
dc.identifierWOS:000336471900005
dc.identifierhttp://dx.doi.org/10.1016/j.cor.2014.02.012
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/924146
dc.descriptionThis study applies a genetic algorithm embedded with mathematical programming techniques to solve a synchronized and integrated two-level lot sizing and scheduling problem motivated by a real-world problem that arises in soft drink production. The problem considers a production process compounded by raw material preparation/storage and soft drink bottling. The lot sizing and scheduling decisions should be made simultaneously for raw material preparation/storage in tanks and soft drink bottling in several production lines minimizing inventory, shortage and setup costs. The literature provides mixed-integer programming models for this problem, as well as solution methods based on evolutionary algorithms and relax-and-fix approaches. The method applied by this paper uses a new approach which combines a genetic algorithm (GA) with mathematical programming techniques. The GA deals with sequencing decisions for production lots, so that an exact method can solve a simplified linear programming model, responsible for lot sizing decisions. The computational results show that this evolutionary/mathematical programming approach outperforms the literature methods in terms of production costs and run times when applied to a set of real-world problem instances provided by a soft drink company. (C) 2014 Elsevier Ltd. All rights reserved.
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.languageeng
dc.publisherElsevier B.V.
dc.relationComputers & Operations Research
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectGenetic algorithms
dc.subjectMathematical programming
dc.subjectMathheuristics
dc.subjectSoft drink industry
dc.subjectProduction planning
dc.subjectLot sizing and scheduling
dc.titleA genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem
dc.typeOtro


Este ítem pertenece a la siguiente institución