Optimization of Tomato Processing and Agrofarm Logistics Through Mathematical Programming

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.