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Optimization of Tomato Processing and Agrofarm Logistics Through Mathematical Programming.

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Title: Optimization of Tomato Processing and Agrofarm Logistics Through Mathematical Programming.
Authors: Adjei, Bernard Atta1 (AUTHOR) bernard.adjei@uenr.edu.gh, Otoo, Dominic1 (AUTHOR), Sebil, Charles2 (AUTHOR), Ackora-Prah, Joseph2 (AUTHOR), Hussain, Manzoor (AUTHOR) manzoor366@gmail.com
Source: Journal of Applied Mathematics. 3/12/2026, Vol. 2026, p1-19. 19p.
Subjects: Mixed integer linear programming, Mathematical programming, Food industry, Sustainable development, Agricultural economics, Food supply management, Agricultural industries, Industrial costs
Abstract: The escalating demand for processed tomato products has heightened the importance of agro‐allied industries, particularly tomato processing, within the global food supply chain. However, a major challenge lies in optimizing production processes to meet this growing demand while minimizing costs efficiently. In this study, we identify and explore optimal decision values that lead to efficient and profitable outcomes by formulating a mixed‐integer linear programming model to analyze the economic sustainability of fresh and processed tomatoes in the agro‐allied industry. This paper gives important information about the dynamics of the tomato supply chain and offers strategies through two distinct analyses. The first analysis model uses production level as a parameter, whereas the second treats it as a variable. For the first analysis, the threshold prices for a box of fresh tomatoes to ensure profitability were GH¢846 ($68.31) and above for farmers and below GH¢900 ($72.75) for the factory. The second analysis allows flexibility in adjusting production levels, enabling farmers to achieve profitability even when the tomato price is GH¢478 ($38.55) or lower. Optimal farm selection, with consideration for proximity to transfer stations, significantly reduces both the total distance traveled (by 5095.00 km) and the number of transportation trips required (208 fewer trips) compared with the existing method. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Applied Mathematics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Optimization of Tomato Processing and Agrofarm Logistics Through Mathematical Programming.
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  Data: <searchLink fieldCode="DE" term="%22Mixed+integer+linear+programming%22">Mixed integer linear programming</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+programming%22">Mathematical programming</searchLink><br /><searchLink fieldCode="DE" term="%22Food+industry%22">Food industry</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainable+development%22">Sustainable development</searchLink><br /><searchLink fieldCode="DE" term="%22Agricultural+economics%22">Agricultural economics</searchLink><br /><searchLink fieldCode="DE" term="%22Food+supply+management%22">Food supply management</searchLink><br /><searchLink fieldCode="DE" term="%22Agricultural+industries%22">Agricultural industries</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+costs%22">Industrial costs</searchLink>
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  Label: Abstract
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  Data: The escalating demand for processed tomato products has heightened the importance of agro‐allied industries, particularly tomato processing, within the global food supply chain. However, a major challenge lies in optimizing production processes to meet this growing demand while minimizing costs efficiently. In this study, we identify and explore optimal decision values that lead to efficient and profitable outcomes by formulating a mixed‐integer linear programming model to analyze the economic sustainability of fresh and processed tomatoes in the agro‐allied industry. This paper gives important information about the dynamics of the tomato supply chain and offers strategies through two distinct analyses. The first analysis model uses production level as a parameter, whereas the second treats it as a variable. For the first analysis, the threshold prices for a box of fresh tomatoes to ensure profitability were GH¢846 ($68.31) and above for farmers and below GH¢900 ($72.75) for the factory. The second analysis allows flexibility in adjusting production levels, enabling farmers to achieve profitability even when the tomato price is GH¢478 ($38.55) or lower. Optimal farm selection, with consideration for proximity to transfer stations, significantly reduces both the total distance traveled (by 5095.00 km) and the number of transportation trips required (208 fewer trips) compared with the existing method. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Applied Mathematics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1155/jama/4918539
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      – Code: eng
        Text: English
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        PageCount: 19
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      – SubjectFull: Mixed integer linear programming
        Type: general
      – SubjectFull: Mathematical programming
        Type: general
      – SubjectFull: Food industry
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      – SubjectFull: Sustainable development
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      – SubjectFull: Agricultural economics
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      – SubjectFull: Food supply management
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      – SubjectFull: Agricultural industries
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      – SubjectFull: Industrial costs
        Type: general
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      – TitleFull: Optimization of Tomato Processing and Agrofarm Logistics Through Mathematical Programming.
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            NameFull: Adjei, Bernard Atta
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              Text: 3/12/2026
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              Y: 2026
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