Fertilizer Logistics in Brazil: Application of a Mixed-Integer Programming Mathematical Model for Optimal Mixer Locations

<i>Background:</i> Brazil is one of the largest consumers of fertilizers and is highly dependent on the international market to meet its demand for agricultural production inputs. The complexity of the fertilizer supply chain motivated us to carry out this study on redesigning the fertil...

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Main Authors: Fernando Pauli de Bastiani, Thiago Guilherme Péra, José Vicente Caixeta-Filho
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Logistics
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Online Access:https://www.mdpi.com/2305-6290/8/1/4
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author Fernando Pauli de Bastiani
Thiago Guilherme Péra
José Vicente Caixeta-Filho
author_facet Fernando Pauli de Bastiani
Thiago Guilherme Péra
José Vicente Caixeta-Filho
author_sort Fernando Pauli de Bastiani
collection DOAJ
description <i>Background:</i> Brazil is one of the largest consumers of fertilizers and is highly dependent on the international market to meet its demand for agricultural production inputs. The complexity of the fertilizer supply chain motivated us to carry out this study on redesigning the fertilizer logistics chain and evaluate strategies for reducing logistics costs by redesigning the fertilizer mixing network in Brazil, a country that is heavily dependent on imported fertilizers for agriculture. <i>Methods:</i> We introduce a multi-product mixed-integer linear programming optimization model encompassing the logistics network, from import ports to mixing factories and agricultural fertilizer supply centers. This model includes logistics infrastructure and taxes, accounting for greenhouse gas emissions (specifically carbon dioxide) in fertilizer logistics. <i>Results:</i> The results indicate that expanding the port capacity for fertilizer importation can significantly reduce logistics costs and greenhouse gas emissions by up to 22.5%, decreasing by 23.9% compared to the baseline. We also observed that removing taxes on fertilizer importation can reduce logistics costs by approximately 11%, but it increases greenhouse gas emissions by 2.25% due to increased reliance on road transport. We identified 15 highly resilient regions for establishing mixing factories, evaluated various scenarios and determined the importance of these locations in optimizing the fertilizer supply network in the country. Moreover, the results suggest a significant potential to enhance the role of Brazil’s Northern Arc region in fertilizer import flows. <i>Conclusions:</i> Public policies and private initiatives could be directed toward encouraging the establishment of mixing factories in the identified regions and increasing transport capacity in the Northern Arc region. Improving the logistical conditions of the fertilizer network would contribute to food security by reducing the costs of essential inputs in food production and promoting sustainability by reducing greenhouse gas emissions.
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spelling doaj-art-77cf3c6372f04dfdb45b0d83585361ac2025-08-20T03:14:53ZengMDPI AGLogistics2305-62902024-01-0181410.3390/logistics8010004Fertilizer Logistics in Brazil: Application of a Mixed-Integer Programming Mathematical Model for Optimal Mixer LocationsFernando Pauli de Bastiani0Thiago Guilherme Péra1José Vicente Caixeta-Filho2Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba 13418-900, BrazilLuiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba 13418-900, BrazilLemann Center for Brazilian Studies, University of Illinois at Urbana-Champaign (UIUC), Champaign, IL 61820, USA<i>Background:</i> Brazil is one of the largest consumers of fertilizers and is highly dependent on the international market to meet its demand for agricultural production inputs. The complexity of the fertilizer supply chain motivated us to carry out this study on redesigning the fertilizer logistics chain and evaluate strategies for reducing logistics costs by redesigning the fertilizer mixing network in Brazil, a country that is heavily dependent on imported fertilizers for agriculture. <i>Methods:</i> We introduce a multi-product mixed-integer linear programming optimization model encompassing the logistics network, from import ports to mixing factories and agricultural fertilizer supply centers. This model includes logistics infrastructure and taxes, accounting for greenhouse gas emissions (specifically carbon dioxide) in fertilizer logistics. <i>Results:</i> The results indicate that expanding the port capacity for fertilizer importation can significantly reduce logistics costs and greenhouse gas emissions by up to 22.5%, decreasing by 23.9% compared to the baseline. We also observed that removing taxes on fertilizer importation can reduce logistics costs by approximately 11%, but it increases greenhouse gas emissions by 2.25% due to increased reliance on road transport. We identified 15 highly resilient regions for establishing mixing factories, evaluated various scenarios and determined the importance of these locations in optimizing the fertilizer supply network in the country. Moreover, the results suggest a significant potential to enhance the role of Brazil’s Northern Arc region in fertilizer import flows. <i>Conclusions:</i> Public policies and private initiatives could be directed toward encouraging the establishment of mixing factories in the identified regions and increasing transport capacity in the Northern Arc region. Improving the logistical conditions of the fertilizer network would contribute to food security by reducing the costs of essential inputs in food production and promoting sustainability by reducing greenhouse gas emissions.https://www.mdpi.com/2305-6290/8/1/4fertilizerslogisticsmixersoptimal locationmathematical programming
spellingShingle Fernando Pauli de Bastiani
Thiago Guilherme Péra
José Vicente Caixeta-Filho
Fertilizer Logistics in Brazil: Application of a Mixed-Integer Programming Mathematical Model for Optimal Mixer Locations
Logistics
fertilizers
logistics
mixers
optimal location
mathematical programming
title Fertilizer Logistics in Brazil: Application of a Mixed-Integer Programming Mathematical Model for Optimal Mixer Locations
title_full Fertilizer Logistics in Brazil: Application of a Mixed-Integer Programming Mathematical Model for Optimal Mixer Locations
title_fullStr Fertilizer Logistics in Brazil: Application of a Mixed-Integer Programming Mathematical Model for Optimal Mixer Locations
title_full_unstemmed Fertilizer Logistics in Brazil: Application of a Mixed-Integer Programming Mathematical Model for Optimal Mixer Locations
title_short Fertilizer Logistics in Brazil: Application of a Mixed-Integer Programming Mathematical Model for Optimal Mixer Locations
title_sort fertilizer logistics in brazil application of a mixed integer programming mathematical model for optimal mixer locations
topic fertilizers
logistics
mixers
optimal location
mathematical programming
url https://www.mdpi.com/2305-6290/8/1/4
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AT josevicentecaixetafilho fertilizerlogisticsinbrazilapplicationofamixedintegerprogrammingmathematicalmodelforoptimalmixerlocations