Logistical transportation routes optimization for Brazilian soybean: an application of the origin-destination matrix

Abstract

The last Brazilian agricultural frontier known as MATOPIBA, an acronym for the states of Maranhão, Tocantins, Piaui and Bahia, is a region that has stood out in the scenario of modern large-scale agriculture intensive in capital and technology. However, barriers related to the transportation system, especially regarding the high logistics costs, have been negatively impacting this sector. To optimize the performance of this chain, a model for minimizing transportation costs was developed, using linear programming with an origin-destination matrix. The purpose of this paper was to evaluate whether the use of the North-South Railroad has potential as a new alternative intermodal route for soybean export from the MATOPIBA region, in order to minimize the transportation costs and promote the viability of new ports located in the northeast region of the country. This configuration can also contribute to reduce the overload of Santos Port (SP). Two scenarios were proposed based on the 2016/17 harvest of soybeanwhere the first scenario (A) consisted only of road routes, while the second (B), in addition to these routes, incorporated road-rail and road-water way intermodal routes. As a result, total transportation cost was reduced by 30% in scenario B and about half of all cargo was shipped by the new intermodal road-rail route to the Itaqui Port in the Northeast region. This configuration promotes a more sustainable logistics chain for soy, with more rational use of transport modes and decentralization of investments to other regions.

Analyzing complexities in the Brazilian soybean supply chain: a systems thinking and modeling approach

“…Logistical bottlenecks, especially the shortage in warehousing (Filippi & Guarnieri, 2019), the inefficient cargo transportation (Silva & D'Agosto, 2013;Reis & Leal, 2015;Oliveira & Alvim, 2017) and transaction cost of ports of export (Esteves et al, 2020) have been analyzed. Optimization models have been dedicated to solving problems of more efficient transport routes for agricultural commodities (Branco, Bartholomeu, Junior, & Caixeta Filho, 2020;Oliveira, Filassi, Lopes, & Marsola, 2021), minimizing the transportation cost for grains (Mogale, Kumar, & Tiwari, 2018), evaluating agricultural exports through simulation models dedicated to transportation (Lopes, Lima, Leal, & Nelson, 2017;Lopes, Lima, & Leal, 2020), and reducing losses of agricultural products in transportation (Nourbakhsh, Bai, Maia, Ouyang, & Rodriguez, 2016;CONAB, 2018).…”