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. / Thesis (M.Sc.)-University of KwaZulu-Natal, 2008.

Long delays between harvesting and crushing of sugarcane lead to excessive deterioration in the quality of sugarcane. The aim of this project was to develop a computer based model of sugarcane harvesting and delivery systems that could be used to investigate methods of reducing harvest-to crush delays. A literature review was conducted and simulation modelling was chosen as the most appropriate modelling technique for the situation of sugarcane harvesting and delivery and the purposes of this project. The Arena modelling system was chosen as the simulation software with which to construct the model. A model was developed on the scale of a particular sugar mill and the area of farms supplying it with cane. The Sezela mill on the south coast of KwaZulu-Natal, South Africa was chosen as a case study on which to develop and test the model. The model integrated a harvesting and transport section which represented all the individual farms or combinations of farms in the area with a millyard section. After the model had been verified and validated, it was used to investigate the effect of a number of different scenarios of harvesting and delivery systems and schedules on harvest-to-crush delays in the Sezela mill area. The results of the experimental runs performed with the model indicated that the most significant decreases in harvest-to-crush delays could be brought about by matching harvesting, delivery and milling cycles as closely as possible. It was also evident that burn-to-cut delays where daily burning is not practised constitute a large proportion of overall harvest-to crush delays. The model proved to be useful in making comparisons between systems and in providing a holistic view of the problem of harvest-to-crush delays. Recommendations for future developments of the model include adding a mechanical harvesting component and making the model more easily applicable to other mill areas. / Thesis (M.Sc.Eng.)-University of Natal, 1998.