The dynamic and volatile nature of the supply chains produce various types of uncertainties along the supply chain, for example demand uncertainty, supply uncertainty, delivery uncertainty and forecasting uncertainty. These uncertainties make supply chains complex and non-linear systems as they propagate along the supply chain in both upstream and down stream. This thesis investigates the dynamic behaviour of a three-echelon supply chain. The modeling of this structure is carried out to display its non-linear dynamic behaviour. It is shown that the dynamics ( stability) of the supply chain is very sensitive to external uncertainties. Specifically, the supply chain subjected to these uncertainties can exhibit strange and undesired states such as saturation and chaos. An active control algorithm for the automatic cancellation of these strange dynamics due to uncertainties is developed by re-adjusting the internal parameters of the supply chain in order to achieve its synchronisation. A bifurcation analysis is carried out. This analysis is essential and useful for decision makers as it allows both the visualisation and control of the states/dynamics of the entire supply chain. The applicability and usefulness of these methods is validated by applying the bifurcation analysis on the tamagotchi supply chain to show how they could have avoided the losses despite the sucess of the product. Planning issues like real-time scheduling in conjunction with dynamic resource allocation especially in face of uncertainties significantly gain in importance in managing the supply chains. In this context, from the area of nonlinear dynamics a novel ultra-fast scheduling scheme involving an emulated "analogue computing" concept based on cellular neural networks is proposed in this thesis for real time planning process.