Meta-Heuristic Approaches for a Soft Drink Industry Problem

dc.contributorUniversidade Federal de Lavras (UFLA)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-10T18:10:17Z
dc.date.accessioned2022-12-19T20:10:28Z
dc.date.available2020-12-10T18:10:17Z
dc.date.available2022-12-19T20:10:28Z
dc.date.created2020-12-10T18:10:17Z
dc.date.issued2008-01-01
dc.identifier2008 Ieee International Conference On Emerging Technologies And Factory Automation, Proceedings. New York: Ieee, p. 1384-+, 2008.
dc.identifier1946-0740
dc.identifierhttp://hdl.handle.net/11449/195920
dc.identifierWOS:000260495500221
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5376557
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.
dc.languageeng
dc.publisherIeee
dc.relation2008 Ieee International Conference On Emerging Technologies And Factory Automation, Proceedings
dc.sourceWeb of Science
dc.titleMeta-Heuristic Approaches for a Soft Drink Industry Problem
dc.typeActas de congresos


Este ítem pertenece a la siguiente institución