Route Optimization Strategies for Enhancing Logistics Efficiency in Agricultural Supply Chains

Abstract

The North Bandung Cattle Breeders Cooperative (KPSBU) plays a pivotal role in the regional dairy industry, yet it faces significant financial discrepancies due to inefficient, intuition-based feed distribution routes. These operational inefficiencies lead to vehicle operating costs (VOC) that consistently exceed the management’s established budgetary standards. This study aims to model and optimize these distribution costs through digital simulation to achieve higher logistical efficiency. The research employs a descriptive quantitative design, utilizing SCM Globe and AnyLogic software to simulate various routing and maintenance scenarios based on historical data. This simulation-based approach allows for the rigorous testing of a "digital twin" environment to identify the most cost-effective logistical strategy without disrupting active operations. The model specifically evaluates 11 distribution points (TPK) in the Lembang area, incorporating variables such as distance, vehicle lifespan, and maintenance requirements. The principal results demonstrate that Scenario 1, focusing on the shortest-path optimization, successfully reduces the VOC to Rp 549,146, yielding a direct saving of Rp 13,277 per trip. The major conclusion is that data-driven route optimization significantly outperforms conventional estimation methods in reconciling actual expenditures with corporate budgets. This study contributes a practical digital supply chain framework that agricultural cooperatives can adopt to enhance financial resilience and asset sustainability in the digital era.