Using fuzzy multiobjective programming to minimize greenhouse gas emissions from crops

• Fuzzy multi-objective model to optimize land use change between agriculture and industry. • Examining the economic and environmental goals among four scenarios in order to optimize land between industry and agriculture. • Obtaining annual profit, carbon footprint and water footprint in the water footprint minimization scenario. • Obtaining annual profit, carbon footprint and water footprint in the carbon footprint minimization scenario. Environmental concerns and food security are growing global concerns. Soy, a staple in Asia, is crucial for dietary needs and global commerce. This research aims to optimize the production of oil and its derivatives in northern Iran for 2022, considering its high significance among leguminous seeds. This study aimed to address the demands of the growing population and ensure food security in the region. This study presents the design of a fuzzy multiobjective MILP model for the purpose of planning sustainable land development in agricultural and industrial value chains. The model considers the anticipated demand and considers four different scenarios. According to the findings, the profit maximization scenario yields an annual profit of 1542,0380 dollars, a carbon footprint of 24,330, and a water footprint of 1524,20,500 dollars per year. Compared with the multiobjective function, the annual profit increases by 46 %, the carbon footprint increases by 44 %, and the water footprint increases by 1524,20,500 dollars. It has had an 88 % growth. In the scenario of minimizing the carbon footprint, the yearly profit is $3842,201, the carbon footprint is measured at 7550, and the water footprint is recorded at 2012,242. The volume of water increased by 90 %. In the scenario aimed at minimizing the water footprint, the yearly profit is $1357,400, the carbon footprint is 21,440, and the water footprint is 1042,152. There was a decrease of 42 %. Based on the findings of the multiobjective model, it is recommended that agricultural areas N1, N3, and N5 be included in the current cultivated area to satisfy the domestic soybean requirements of the nation. Additionally, it is recommended to construct a new factory together with a corresponding refinery for the production of edible soybean oil. Additionally, the inclusion of a Fac 10 soybean meal processing unit is recommended for the system.

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Publication Details

Journal
Results in Engineering
Published
2025-11-21
DOI
https://doi.org/10.1016/j.rineng.2025.108265
Primary Topic
Optimization and Mathematical Programming
Type
article
Field-Weighted Citation Impact
0.00
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article

Using fuzzy multiobjective programming to minimize greenhouse gas emissions from crops

Ali Koochi, Mohammad Reza Gharib, Masoud Goharimanesh, Fatemeh Rastegarpour
Results in Engineering
Optimization and Mathematical Programming
article

Using fuzzy multiobjective programming to minimize greenhouse gas emissions from crops

Ali Koochi, Mohammad Reza Gharib, Masoud Goharimanesh, Fatemeh Rastegarpour
article en

Abstract

• Fuzzy multi-objective model to optimize land use change between agriculture and industry. • Examining the economic and environmental goals among four scenarios in order to optimize land between industry and agriculture. • Obtaining annual profit, carbon footprint and water footprint in the water footprint minimization scenario. • Obtaining annual profit, carbon footprint and water footprint in the carbon footprint minimization scenario. Environmental concerns and food security are growing global concerns. Soy, a staple in Asia, is crucial for dietary needs and global commerce. This research aims to optimize the production of oil and its derivatives in northern Iran for 2022, considering its high significance among leguminous seeds. This study aimed to address the demands of the growing population and ensure food security in the region. This study presents the design of a fuzzy multiobjective MILP model for the purpose of planning sustainable land development in agricultural and industrial value chains. The model considers the anticipated demand and considers four different scenarios. According to the findings, the profit maximization scenario yields an annual profit of 1542,0380 dollars, a carbon footprint of 24,330, and a water footprint of 1524,20,500 dollars per year. Compared with the multiobjective function, the annual profit increases by 46 %, the carbon footprint increases by 44 %, and the water footprint increases by 1524,20,500 dollars. It has had an 88 % growth. In the scenario of minimizing the carbon footprint, the yearly profit is $3842,201, the carbon footprint is measured at 7550, and the water footprint is recorded at 2012,242. The volume of water increased by 90 %. In the scenario aimed at minimizing the water footprint, the yearly profit is $1357,400, the carbon footprint is 21,440, and the water footprint is 1042,152. There was a decrease of 42 %. Based on the findings of the multiobjective model, it is recommended that agricultural areas N1, N3, and N5 be included in the current cultivated area to satisfy the domestic soybean requirements of the nation. Additionally, it is recommended to construct a new factory together with a corresponding refinery for the production of edible soybean oil. Additionally, the inclusion of a Fac 10 soybean meal processing unit is recommended for the system.

Results in EngineeringVol. 28
University of Torbat Heydarieh (IR)
Openalex Percentile: Top 56%
Optimization and Mathematical Programming
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