| dc.description.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. | en_US |
