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Type: Artigo
Title: A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem
Author: Toledo, C. F. M.
Morabito, R.
de Oliveira, L.
Pereira, R. D.
Franca, P. M.
Abstract: This 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
Subject: Algoritmos genéticos
Programação matemática
Refrigerantes - Indústria
Country: Reino Unido
Editor: Elsevier
Rights: Fechado
Identifier DOI: 10.1016/j.cor.2014.02.012
Date Issue: 2014
Appears in Collections:FEEC - Artigos e Outros Documentos

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