<![CDATA[In the logistics sector, distribution plays a crucial role as it directly affects operational costs and delivery time efficiency. The Sidoarjo Branch Post Office is one of the logistics service providers with a wide delivery coverage area. However, it still faces several issues, particularly suboptimal delivery routes and an imbalance in workload distribution among couriers. Therefore, this study aims to optimize delivery routes by considering vehicle capacity and workload balancing using the Capacitated Vehicle Routing Problem (CVRP) approach combined with a Genetic Algorithm. The Genetic Algorithm was selected due to its ability to explore a wide solution space and avoid being trapped in local optima. The process includes population initialization, fitness evaluation, selection, crossover, mutation, and the generation of new populations. The CVRP model is applied to minimize total travel distance while considering constraints such as vehicle capacity, customer visits, and workload distribution among couriers. The results show that the proposed approach produces shorter delivery routes compared to the manual method, achieving a distance reduction of 19.9%. In addition, the number of required couriers is reduced from 13 to 10 without exceeding capacity constraints. The developed web-based decision support system is able to present comparisons before and after optimization, distribute workloads more evenly, reduce the number of active couriers, and provide route recommendations for each courier. Overall, the proposed approach proves to be effective in improving operational efficiency and performance at the Sidoarjo Branch Post Office.]]>
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