<![CDATA[Distribution activities at PT Rezeki Surya Gasindo face challenges due to limited vehicle capacity and uncertain customer demand, which complicate route planning and may affect distribution performance. This study aims to model and optimize the Split Delivery Vehicle Routing Problem (SDVRP) under demand uncertainty. The problem is formulated using Integer Linear Programming (ILP), where demand uncertainty is incorporated into the optimization framework to ensure that the resulting solutions remain feasible under varying customer demands. The model is implemented using Python with the PuLP library and further solved using a Genetic Algorithm based on the company’s distribution data. The results show that the proposed SDVRP model produces a distribution plan with a minimum total travel distance of 54.60 km. The optimal solution consists of two main routes: Route 1 serves Depot – Jalan Baru – Talang Gulo – Depot with a total delivery of 20 cylinders, while Route 2 serves Depot – Talang Gulo – Jeramba Bolong – Jambi Timur – Depot with a total delivery of 20 cylinders. These results demonstrate the applicability of the proposed SDVRP model in generating feasible distribution routes under demand uncertainty.]]>
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