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A three-stage stochastic optimization model for the Brazilian biodiesel supply chain

Abstract

The Brazilian program for biodiesel use highlights the production of biodiesel from castor seeds. Biodiesel is a non-polluting energy source that has the potential to promote prosperity by creating jobs in poor regions of Brazil. However, the infrastructure, logistics, and proper facilities are lacking. A variety of approaches to optimizing the biodiesel supply chain have been proposed. The goal is to minimize the grain storage and transportation costs. This paper presents a comparison between a two-stage model and a multistage (three-stage) stochastic model to optimize the biodiesel supply chain. The comparison between these formulations shows that the flexibility gain provided by the multistage model results in a lower total logistic cost. The optimum for the three-stage model was 7,700,019 (BRL), compared to 8,628,002 (BRL) for the two-stage model, representing a savings of 927,983 (BRL). We highlight that this model offers a real solution for castor supply chain design (considering uncertainty) in the Brazilian semiarid region, which is a poorer region of the country, thus making cost reduction mandatory.

Keywords
Biodiesel; Mixed Integer Linear programming; Stochastic optimization; Multistage program

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