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Model for Estimating the Demand for Soybean Railway Transport in Brazil’s Logistic Corridors Under Competitive Conditions

In: Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry

Author

Listed:
  • Thiago Guilherme Péra

    (University of São Paulo)

  • Abner Matheus João

    (University of São Paulo)

  • José Vicente Caixeta Filho

    (University of São Paulo)

Abstract

The state of Mato Grosso, Brazil’s largest grain producer, presents a logistical deficit that reduces its competitivity for having a unique rail solution that is located in its state, “Rumo Malha Norte” (RMN) transhipment terminal in Rondonópolis (MT). In that way, the railway system expansion presents a major role for logistic cost reduction. The objective of this paper was to present a comparative analysis for the current and prospected corridor solutions for Mato Grosso’s state grain exportation market, considering the demand calculation for each railway and the impact on total cost reduction in order to define the best investment option for the public and private actors. For achieving the results, it was structured a six-step algorithm that considered roadway freight prices and had the scenarios built upon discounts for composing the rail transportation prices. In terms of cargo capturing, Ferrogrão railway has the highest potential for the state, although RMN expansion to the municipalities of Cuiabá (MT), Nova Mutum (MT), or Lucas do Rio Verde (MT) also presents good results. Furthermore, the best solutions (Ferrogrão and all three RMN expansions) were compared, and Ferrogrão project is also more sensible to reductions in rail freight prices over roadway transportation, leading to lower total costs for the actors in the market.

Suggested Citation

  • Thiago Guilherme Péra & Abner Matheus João & José Vicente Caixeta Filho, 2024. "Model for Estimating the Demand for Soybean Railway Transport in Brazil’s Logistic Corridors Under Competitive Conditions," Springer Books, in: Víctor M. Albornoz & Alejandro Mac Cawley & Lluis M. Plà-Aragonés (ed.), Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry, pages 29-34, Springer.
  • Handle: RePEc:spr:sprchp:978-3-031-49740-7_2
    DOI: 10.1007/978-3-031-49740-7_2
    as

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