최적 운송물량 분할방식의 수송경로에 따른 운송비용 최적해법

Cargo transportation possesses unique characteristics influenced by factors such as product type, origin-to-destination dynamics, fluctuating demand, time constraints, market conditions, competition, production volume fluctuations, product pricing, and transportation costs. These factors significantly impact a company's transportation policies and decision-making processes. The transportation problem can be seen as a minimum cost flow problem utilized in intricate scenarios involving multiple supply and demand locations, each with distinct volumes of supply and demand, along with specific unit delivery costs. The system comprises a total of supply points and (n) demand points, with varying supply amounts at each supply point and corresponding demands at the respective demand points. Additionally, each unit of shipment incurs a specific shipping cost . This study primarily focuses on the costs associated with transporting raw materials to manufacturing plants for product creation and the subsequent shipping costs involved in delivering the finished products to customers. Hence, developing a distribution and allocation plan that effectively minimizes transportation modeling costs is of utmost importance. To achieve an optimal solution, this study adopts an experimental approach by dividing the transportation volume based on the transportation route for raw materials delivery and subsequent product shipping. Cluster1 conducted an experiment to derive the optimal solution for the total transportation cost of the entire quantity within the experimental model. Cluster2 and Cluster3 utilized the transport volume distribution allocation method and implemented the DBSA algorithm to divide the vehicle route. The test subject was divided into two or three segments, and the evaluation of the total cost was performed for scenarios where =1,2,3.