The rice supply chain in Indonesia plays a vital role in national food security, where efficient distribution ensures price stability and availability in the market. However, the complexity of multi-echelon systems often leads to inefficiencies in procurement, production, and distribution. This study aims to develop a Mixed-Integer Linear Programming (MILP) model to optimize the rice supply chain in Karawang Regency, focusing on cost minimization while integrating environmental and risk considerations. Using dummy data on supply, demand, production, distribution, labor, and emissions, the model was tested with Microsoft Excel Solver. The results show that procurement from farmer groups is the largest cost component (51.24%), followed by production (23.96%) and distribution (23.19%), with a total cost of USD 1,783,113,142. Optimization achieved a 13% cost reduction and a 9% emission reduction compared to non-optimized conditions, while risk assessment identified M2–J2 supply (RPN = 20) and J1 production (RPN = 16) as the most critical hazards. These findings suggest practical implications for Perum Bulog and policymakers, including strengthening procurement planning, optimizing warehouse allocation, and adopting cleaner production technologies to improve both efficiency and sustainability. The novelty of this study lies in integrating hazard-based risk assessment with MILP for a regionally strategic rice supply chain, while simultaneously considering cost efficiency and carbon emission constraints. This provides both theoretical contributions to sustainable supply chain optimization and practical strategies for policy driven food security.
Mansur et al. (Mon,) studied this question.
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