Close-Open Mixed Vehicle Routing Optimization Model with Multiple Collecting Centers to Collect Farmers' Perishable Produce

Today, there is a tendency towards promoting locally produced perishable products along the supply chain. Due to the short shelf-life, it is necessary to optimize collecting perishable goods to reduce wastage. The research attempt to solve a problem where internal and hired trucks are used to collect perishable goods. The proposed Vehicle Routing Problem (VRP) is different from the classical VRP and comprises both close and open routes. The problem is known as Close-Open Mixed Vehicle Routing Problem (COMVRP). The proposed model uses both internal and hired fleets with heterogeneous capacities. The internal trucks start from the multiple collecting centres and return to the origin point after completing the task. Further, hired trucks start from the third-party locations and return to the assigned collecting centre to store the goods. A Greedy algorithm-based heuristic was used to obtain the initial solutions. Moreover, several local search methods, including Guided Local Search (GLS), Simulated Annealing (SA), and Tabu Search (TS), were used to obtain the near-optimal solutions for the proposed problem. The research employed data from a real-world case study to conduct the numerical experiments in OR Tools. The results of the numerical experiments indicate that GLS outperforms in solving the proposed problem. Moreover, GLS obtained near-optimal solutions in reasonable computation time. Analysis showed that the proposed model is achieved more than 80% of truck capacity utilization. The proposed model assists industry practitioners to mitigate transport inefficiencies. Thereby it helps to minimize post-harvest wastage during the collection process. A further study compared real-driving distance and the Euclidean distance as input data. It is noted that when Euclidean distances are used, the algorithms fail to reach the optimal solutions.