Journal
COMPUTERS & OPERATIONS RESEARCH
Volume 48, Issue -, Pages 40-52Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2014.02.012
Keywords
Genetic algorithms; Mathematical programming; Mathheuristics; Soft drink industry; Production planning; Lot sizing and scheduling
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Funding
- Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) [483474/2013-4]
- Fundacao de Amparo Pesquisa do Estado de Sao Paulo (FAPESP) [2010/10133-0]
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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.
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