Mixed Integer Linear Programming for Sugarcane Truck Scheduling

Abstract

  Sugarcane supply, as the primary raw material in sugar production, is the most important component for a sugarmill. If an excessive amount of sugarcane is delivered to the factory, it may lead to prolonged storage, resulting in significant yield losses. Thus, it is necessary to synchronize sugarcane intake with milling capacity. Sugarcane truck scheduling mathematical models can improve the efficiency of the sugarcane transportation process. This research focused on addressing the sugarcane truck scheduling problem, using a case study of a sugarmill to optimize the scheduling and sequencing of sugarcane trucks for dump tippler machines. The objective function is to minimize total time in terms of transportation and dumping time. This work presents a Mixed Integer Linear Programming (MILP) model for solving the truck scheduling problem. The results of this study reveal that the minimum total time is 15,144 minutes, demonstrating the potential of the proposed model. The results obtained can help improve the inbound logistics of sugarcane in the sugar industry.