<![CDATA[Efficient crude palm oil (CPO) distribution is essential for maintaining the competitiveness of vertically integrated palm oil industries. This study addresses a multi-origin, multi-echelon CPO distribution problem involving 37 internal palm oil mills, external suppliers, dual operational hubs, and refinery capacity constraints at PT Industri Nabati Lestari (INL). A multi-period Mixed Integer Linear Programming (MILP) model is developed within a Minimum Cost Flow (MCF) framework to optimize CPO allocation to INL and Belawan Port. The model incorporates daily production data over a one-year horizon, refinery throughput limits, inventory carry-over, binary operational decisions, and transportation costs. The model was solved using the HiGHS solver with a Branch-and-Cut algorithm across nine refinery-throughput scenarios ranging from 1,800 to 4,500 tons/day (40%–100% utilization), comprising 108 monthly sub-problems. All sub-problems reached true optimality with a final MIP gap of 0.00%, with an average runtime of approximately one minute per sub-problem. Under the representative Q = 1,800 tons/day scenario, which most closely reflects the company’s 2025 operating conditions, the optimized annual logistics cost was Rp335.46 billion, with a unit transportation cost of Rp129.78/kg, compared with the historical cost of Rp162.58/kg, representing a reduction of Rp32.80/kg or 20.2%. At Q = 4,500 tons/day, the annual transportation cost decreased to Rp308.49 billion. The results demonstrate that prioritizing low-cost internal suppliers while using external suppliers to compensate for seasonal shortages can reduce transportation costs. The proposed framework provides decision support for supply allocation, inventory planning, transportation management, and refinery capacity utilization in large-scale palm oil supply chains.]]>
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