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A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem

Motta Toledo, Claudio Fabiano ; de Oliveira, Lucas ; de Freitas Pereira, Rodrigo ; França, Paulo Morelato ; Morabito, Reinaldo

Computers & operations research, 2014-08, Vol.48, p.40-52 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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Título:
A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem
Autor: Motta Toledo, Claudio Fabiano ; de Oliveira, Lucas ; de Freitas Pereira, Rodrigo ; França, Paulo Morelato ; Morabito, Reinaldo
Assuntos: Applied sciences ; Biological and medical sciences ; Bottling ; Decisions ; Exact sciences and technology ; Food industries ; Fundamental and applied biological sciences. Psychology ; Genetic algorithms ; Inventory control, production control. Distribution ; Inventory management ; Lot sizing ; Lot sizing and scheduling ; Mathematical models ; Mathematical programming ; Mathheuristics ; Non alcoholic beverage industries and mineral waters ; Operational research and scientific management ; Operational research. Management science ; Production costs ; Production planning ; Production scheduling ; Raw materials ; Scheduling, sequencing ; Soft drink industry ; Soft drinks ; Studies
É parte de: Computers & operations research, 2014-08, Vol.48, p.40-52
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SourceType-Scholarly Journals-1
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Descrição: 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. •We propose a genetic algorithm with mathematical programming to solve a two-level lot sizing and scheduling problem that arises in soft drink production.•The genetic algorithm defines sequencing decisions and a linear programming model defines lot sizing.•This approach is evaluated in instances from real data provided by a soft drink company.•The method outperforms literature approaches applied to the same problem in terms of solution quality and runtimes.
Editor: Kidlington: Elsevier Ltd
Idioma: Inglês

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A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem

Motta Toledo, Claudio Fabiano ; de Oliveira, Lucas ; de Freitas Pereira, Rodrigo ; França, Paulo Morelato ; Morabito, Reinaldo

Kidlington: Elsevier Ltd

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