Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/75865
Type: Artigo de periódico
Title: A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem
Author: Toledo, CFM
de Oliveira, L
Pereira, RD
Franca, PM
Morabito, R
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. (C) 2014 Elsevier Ltd. All rights reserved.
Subject: Genetic algorithms
Mathematical programming
Mathheuristics
Soft drink industry
Production planning
Lot sizing and scheduling
Country: Inglaterra
Editor: Pergamon-elsevier Science Ltd
Rights: fechado
Identifier DOI: 10.1016/j.cor.2014.02.012
Date Issue: 2014
Appears in Collections:Unicamp - Artigos e Outros Documentos

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