The development of a swarm intelligent simulation tool for sugarcane transport logistics systems.

Abstract

Transport logistics systems typically evolve as networks over time, which may result in system rigidity and cause changes to become expensive and time consuming. In this study a logistics model, named TranSwarm, was developed to simulate sugarcane harvesting, transport and mill-yard activities for a mill supply area. The aim was to simulate produce flow, and allow individual working entities to make decisions, driven by rules and protocols, based on their micro-environments. Noodsberg mill was selected as a case study because of low current levels of synchronization. Growers were assumed to operate independent harvesting and transport systems causing inconsistent convergences at the mill. This diverse and fragmented system provided a suitable environment to construct a model that would consider interactions between individual growers and their respective transport systems. Ideally, by assessing the micro-decisions of individuals and how they influence the larger holistic supply chain, TranSwarm quantifies the impacts of different types of transport practices, such as staggering shift changes, transport scheduling, core sampling and consortium-based logistics. TranSwarm is visual, mechanistic and represents key entities, such as roads, farm groupings and the mill. The system uses discrete events to create a dynamic and stochastic environment from which observations and conclusions can be drawn. This approach potentially allows stakeholders to identify key components and interactions that may jeopardize overall efficiency and to use the system to test new working protocols and logistics rules for improving the supply chain.