TRAVELING SALESMAN PROBLEM WITH PRIORITIZATION FOR PERISHABLE PRODUCTS IN YOGYAKARTA, INDONESIA
The Traveling Salesman Problem (TSP) is challenging, especially when multiple nodes have varied opening hours and the product is perishable. Due to some nodes' inconsistent store opening times, truck drivers frequently reroute on those same networks. This study proposes the TSP model to resolve the distribution problem based on a case study of a bakery distributor's small and medium enterprises (SMEs) in Yogyakarta, Indonesia. This study proposed the TSP model to solve two conditions: the classical and the weighted TSP model. A classical TSP model was for unprioritized nodes, and the weighted TSP model was for the distribution problem, considering the prioritized nodes due to the opening hours of nodes or depots starting in the early morning or afternoon. Therefore, this model aims to minimize the distance travelled by finding the optimum sequence delivery nodes on tour for classical and weighted TSP. To achieve the objective, some experiments using genetic algorithms were employed. Based on the result of experimenting with the proposed model using GA, the total distance-saving improvements for the classical and weighted TSP models were about 46.68% and 45.74%, respectively. The proposed model can help a driver truck decide the product's sequence delivery nodes.