Meta-heuristic approaches for a soft drink industry problem

dc.contributorUniversidade Federal de Lavras (UFLA)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:23:42Z
dc.date.available2014-05-27T11:23:42Z
dc.date.created2014-05-27T11:23:42Z
dc.date.issued2008-11-24
dc.identifierIEEE Symposium on Emerging Technologies and Factory Automation, ETFA, p. 1384-1391.
dc.identifierhttp://hdl.handle.net/11449/70638
dc.identifier10.1109/ETFA.2008.4638579
dc.identifier2-s2.0-56349167064
dc.description.abstractThe present paper evaluates meta-heuristic approaches to solve a soft drink industry problem. This problem is motivated by a real situation found in soft drink companies, where the lot sizing and scheduling of raw materials in tanks and products in lines must be simultaneously determined. Tabu search, threshold accepting and genetic algorithms are used as procedures to solve the problem at hand. The methods are evaluated with a set of instance already available for this problem. This paper also proposes a new set of complex instances. The computational results comparing these approaches are reported. © 2008 IEEE.
dc.languageeng
dc.relationIEEE Symposium on Emerging Technologies and Factory Automation, ETFA
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectBeverages
dc.subjectDiesel engines
dc.subjectFactory automation
dc.subjectGenetic algorithms
dc.subjectHeuristic methods
dc.subjectSemiconductor quantum dots
dc.subjectSystems analysis
dc.subjectTabu search
dc.subjectAnd genetic algorithms
dc.subjectComputational results
dc.subjectHeuristic approaches
dc.subjectIn lines
dc.subjectLot sizings
dc.subjectReal situations
dc.subjectSoft drinks
dc.subjectThreshold accepting
dc.subjectProblem solving
dc.titleMeta-heuristic approaches for a soft drink industry problem
dc.typeActas de congresos


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