Vehicle Routing And Integrated Planning And Scheduling For Perishable Products: A Case Study Of Vinamilk

Abstract

This study addresses the integrated production planning and scheduling problem in the dairy industry after considering the multi-depot vehicle routing problem. The research methodology involves implementing a Genetic Algorithm (GA) to minimize transportation costs by optimizing routes, vehicles, and distances, while ensuring vehicle capacity limitations. The objective is to determine the appropriate depot for serving a specific set of customers, while also considering the plant's awareness of demand fulfillment for each distribution center. The outcomes of the preliminary phase, utilizing GA, are then used in the subsequent stage, which involves formulating a Mixed Integer Linear Programming (MILP) model. This model aims to find an optimal solution that minimizes the total cost, encompassing factors such as product value deterioration, production, inventory, changeover, waste, overtime, packaging, incubation operations, and unmet demand. By employing this approach, the study successfully derives an optimal weekly schedule in a short computational time.