The subject matter of this thesis is the modelling and analysis of serial supply chain (SC) behaviour in an uncertain environment. Main sources of uncertainty inherent in a serial SC and its environment have been identified, including customer demand, external supplier reliability, supply along the chain and lead times. A new approach to modelling and treating these uncertainties based on fuzzy sets theory has been proposed. It has been shown that the application of fuzzy sets is useful in cases where there is lack of available data about SC parameters, lack of certainty in data or when data does not exist. A new original approach to SC analysis has been developed and implemented using C++ programming language. In this approach, two types of models have been combined: (1) SC fuzzy, analytical models and (2) SC simulation models. The new SC fuzzy analytical models have been developed which treat different SC uncertainties simultaneously. In these models, order-up-to levels for all inventories along an SC are determined in such a way as to minimise total possible inventory costs over a given time. Two SC control strategies which take into consideration different uncertainties and reflect different levels of SC integration have been proposed and built into the SC fuzzy models, including: (1) fully decentralised control, and (2) a new developed strategy of partially coordinated control. The aim of the new SC simulation models developed is to evaluate SC performance achieved by applying order-up-to levels and replenishment quantities recommended by the fuzzy models. The SC fuzzy and simulation models, working in a coordinated manner, have been used to gain further insight into SC dynamic behaviour and its performance in an uncertain environment, and to enhance decision making on SC control parameters in the presence of uncertainty. The application of the developed SC tool in the various analyses has been demonstrated, including: (1) quantification and comparison of SC performance under different control strategies, such as decentralised and partially coordinated control, (2) quantification of the effects of changing uncertainty in SC data (e. g., customer demand) on SC behaviour and its, performance, (3) analysis of the effects of uncertainty in external supplier reliability and investigation of the ways of making an SC less vulnerable to this uncertainty, and (4) application of two new procedures for one-site and multi-site compensation which have been developed to compensate for the negative effects of uncertainty in external supply.