AlgoRoute
AI-Driven Logistics Route Planning System at JNU
AlgoRoute: AI-Driven Logistics Route Planning System at JNU (Jun 2021 - Oct 2021)
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This project focused on optimizing logistics routes by employing advanced algorithms. The experiments conducted using Python identified optimal solutions for improving supply chain efficiency, achieving significant time and cost savings.
- Performed Python-based experiments to identify optimal algorithms for improving supply chain route efficiency.
- Utilized diverse algorithms like taboo, adaptive large neighborhood, ant colony, and genetic algorithm to achieve a 35% time reduction and 23% cost savings in route planning compared to single-algorithm applications.
- Optimized routes with customers’ parameters like time windows, vehicle capacity, and vehicle transportation costs.