Efficient Agricultural Logistics Optimization: Leveraging Exact Methods and Genetic Algorithm Based Approaches for Solving MDHFVRP

This study investigates the Multi-Depot Heterogeneous Fleet Vehicle Routing Problem (MDHFVRP) within the context of agricultural logistics optimization. The primary objective is to enhance the efficiency of agricultural product distribution by evaluating and comparing exact methods and genetic algorithm-based approaches. The study demonstrates that while exact methods provide optimal solutions for smaller instances, genetic algorithms exhibit superior performance in handling large-scale instances due to their robustness and scalability. Furthermore, the development of a Vehicle Routing Solver (VRS) interface facilitates practical logistics planning, offering a user-friendly tool for real-world applications.