Meta-Heuristic Approaches for a Soft Drink Industry Problem
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Data
2008-01-01
Autores
Motta Toledo, Claudio Fabiano
Ferreira de Jesus Filho, Jose Euripedes
Franca, Paulo Morelato [UNESP]
Fay, I. A.
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Ieee
Resumo
The 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.
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2008 Ieee International Conference On Emerging Technologies And Factory Automation, Proceedings. New York: Ieee, p. 1384-+, 2008.