<![CDATA[General Background: Efficient distribution planning is essential to ensure timely delivery with reasonable operational costs. Specific Background: PT. ABC distributes gym equipment, with dumbbells as a high-demand product, yet its current route planning is not optimal, leading to longer travel time and higher distribution costs using pick-up trucks. Knowledge Gap: Prior route optimization approaches in similar contexts often emphasize distance reduction without explicitly incorporating vehicle load capacity, reducing realism for heavy-goods delivery. Aims: This study aims to determine an optimal capacitated distribution route for gym dumbbell deliveries at PT. ABC using a Genetic Algorithm within a Capacitated Vehicle Routing Problem (CVRP) framework to minimize total travel distance and distribution cost. Results: The proposed Genetic Algorithm solution produced four delivery routes totaling 174 km compared with the company’s 253.3 km, reducing distance by 79.3 km (31.3%) and lowering total distribution cost from IDR 313,300 to IDR 234,000, a reduction of IDR 79,300 (25.3%). Novelty: Vehicle load capacity is treated as an additional decision variable, making the optimized routes more representative of actual dumbbell distribution conditions. Implications: The findings support managerial decision-making for route planning, operational cost control, and transport fleet productivity, and demonstrate the suitability of Genetic Algorithms for CVRP-based distribution route optimization with realistic capacity considerations. Highlights: Total travel distance decreased by 79.3 km with 31.3% savings versus the existing routing approach. Total delivery expenditure declined by IDR 79,300, equivalent to 25.3% cost savings. Capacity-constrained routing produced four feasible delivery routes aligned with pick-up load limits. Keywords: Genetic Algorithm, Distribution Costs, Capacitated Vehicle Routing Problem, Optimal Route]]>
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