Optimizing Logistics and Fleet Management in Supply Chains Using Cloud-Based Route Planning
Abstract
Efficient logistics and fleet management are essential for minimizing transportation costs and improving delivery timelines. This paper introduces a cloud-based route optimization framework that uses real-time traffic data, weather conditions, and delivery priorities to generate optimal routes. Machine learning models continuously adjust routes based on changing conditions and delivery performance. Performance tests demonstrate reduced delivery times, lower fuel consumption, and improved customer satisfaction. The study concludes that cloud-based route optimization enhances logistics efficiency and reduces operational costs in supply chain management.
References
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