<![CDATA[Fertiliser distribution in palm oil plantations poses a complex Vehicle Routing Problem (VRP) due to dispersed customer locations, limited vehicle capacity, and high transportation costs. While metaheuristic approaches such as Genetic Algorithms (GA) and Ant Colony Optimisation (ACO) are widely used, they typically require extensive parameter tuning and are computationally intensive. The use of Tabu Search in practical plantation logistics, especially under capacity constraints, has been relatively limited. This study aims to optimize fertilizer distribution routes at PT. XYZ using a Tabu Search algorithm. An initial feasible solution is generated using the Nearest Neighbour method and subsequently improved through neighbourhood exploration with tabu memory. The model is implemented in MATLAB 2016 and utilizes operational data, including distance matrices, customer demand, and vehicle capacity constraints. The results indicate a reduction in total travel distance from 4,287 km to 3,618.5 km. Diesel consumption decreases by 15.59%, from 714.5 to 603.08 liters, resulting in cost savings of IDR 757,633. This reduction corresponds to approximately 298 kg of CO2 emissions avoided, thereby supporting more sustainable agricultural logistics. These outcomes contribute directly to climate change mitigation (SDG 13) and promote sustainable resource utilization (SDG 12). Collectively, the findings highlight the effectiveness of Tabu Search as a practical and sustainable optimization method for fertilizer distribution in palm oil plantations. Contribution to Sustainable Development Goals (SDGs):SDG 12: Responsible Consumption and ProductionSDG 13: Climate Action ]]>
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