Evolutionary algorithms application in the optimization of a cut of a paper supply chain
DOI:
https://doi.org/10.5585/exactaep.2021.16318Keywords:
Evolutionary algorithms, Particle swarm optimization, Genetic algorithm, Supply chainAbstract
In a global scenario getting more and more competitive for companies, the concern about the reduction of operational costs is growing. Therefore, the adoption of optimization tools by companies is constant, since they search, in mathematical methods, opportunities to improve current processes. This article aims to evaluate the performance of two evolutionary algorithms in the costs optimization of a supply chain, focusing on materials acquisition costs, storing costs and missed sales costs. For this study, it was analyzed a part of a paper supply chain, considering its product with the biggest income, its first layer suppliers and its first layer clients. One of the algorithms was effective compared to the company’s current purchasing policy, bringing a 3,9%, on the other hand, the other one presented a less favorable result to the company, raising its costs in 74,4%. The optimal solution resulted in a saving of 7,2% compared to what the company practiced.
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