Using agent-based simulation to explore sugarcane supply chain transport complexities at a mill scale

Abstract

The sugarcane supply chain (from sugarcane grower to mill) have particular challenges. One of these is that the growers have to deliver their cane to the mill before its quality degrades. The sugarcane supply chain typically consists of many growers and a mill. Growers deliver their cane daily during the milling season; the amount of cane they deliver depends on their farm size. Growers make decisions about when to harvest the cane, and the number and type of trucks needed to deliver their cane. The mill wants a consistent cane supply over the milling season. Growers are sometimes affected long queue lengths at the mill when they offload their cane. A preliminary agent-based simulation model was developed to understand this complex system. The model inputs a number of growers, and the amount of cane they are to deliver over the milling season. The number of trucks needed by each grower is determined by the trip, loading and unloading times and the anticipated waiting time at the mill. The anticipated waiting time was varied to determine how many trucks would be needed in the system to deliver the week’s cane allocation. As the anticipated waiting time increased, the number of trucks needed also increased, which in turn delayed the trucks when queuing at the mill. The growers’ anticipated waiting times never matched the actual waiting times. The research shows the promise of agent-based models as a sense-making approach to understanding systems where there are many individuals who have autonomous behaviour, and whose actions and interactions can result in unexpected system-level behaviour.