Meta-heuristic approaches for a soft drink industry problem
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Undergraduate course
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Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Type
Work presented at event
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Acesso aberto
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Abstract
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. © 2008 IEEE.
Description
Keywords
Beverages , Diesel engines , Factory automation , Genetic algorithms , Heuristic methods , Semiconductor quantum dots , Systems analysis , Tabu search , And genetic algorithms , Computational results , Heuristic approaches , In lines , Lot sizings , Real situations , Soft drinks , Threshold accepting , Problem solving
Language
English
Citation
IEEE Symposium on Emerging Technologies and Factory Automation, ETFA, p. 1384-1391.
