Document Type : Article-Based Dissertations

Authors

• BAtoul Mislemi ¹
• Ebrahim Moradi ²
• Seyed Mahdi Hosseini ³
• Mahdi Jafari ⁴

¹ PhD student, Faculty of Economics and Management, University of Sistan and Baluchistan

² Faculty of Agricultural Economics, University of Sistan and Baluchestan

³ Faculty of Agricultural Economics, Faculty of Economics and Management, University of Sistan and Baluchistan

⁴ Graduated in Agricultural Economics, Faculty of Economics and Management, University of Sistan and Baluchistan

Abstract

The imbalance between supply and demand for tomatoes in Iran is a multifaceted problem that requires collaboration among farmers, the government, processing industries, and other stakeholders. The objective of this research is to optimize the centralized and distributed cultivation of tomatoes in southern Kerman Province. To compare economic parameters (objective function and profit) under deterministic and uncertain conditions across different scenarios, distributed and centralized mathematical programming models were used. The mathematical programming model for tomato supply was analyzed in four scenarios (distributed and centralized): lack of collaboration among farmers (A), land constraints (B), information exchange with government institutions (S), and centralized decision-making (C). The data used in this study were collected through questionnaires and interviews with major tomato farmers from 2020 to 2023 in three counties: Jiroft, Anbarabad, Kahnuj, and Rudbar-e Jonub.

Based on the examined scenarios, the results indicated that scenario S is the closest to optimal conditions, suggesting that shared information on demand is sufficient for farmer collaboration. In scenario A, the lack of attention to market demand and the absence of any constraints on the cultivation area for each variety led to unfavorable conditions for tomato supply. Additionally, the results under uncertain conditions were consistent with those under deterministic conditions, but all scenarios performed better under uncertainty compared to deterministic conditions. Based on the findings of this study, it is recommended that, given the similarity in the objective function and profit per hectare between scenarios S and C, an appropriate solution for optimizing tomato cultivation is to preserve farmers' independence and implement a distributed model that collects minimal demand-related information proportional to the farmers' land area and shares it only with a central coordinator (scenario S).

Keywords

• Optimization
• Tomato
• Uncertainty
• South Kerman