Existing simulation tools are able to map large size supply chains and can accommodate complex random phenomena. Nevertheless, they have significant weakness in the power of decision-making. Indeed, most of the problems of decision-making are typically determined by simplified rules. For this reason, involving optimisation tools in decision-making will allow the simulation to explore the real performance of a supply chain. Motivated by the limitations of existing supply chains simulation and optimisation tools, the aim of this study is to combine them in a single tool. More specifically, we aim to develop an 'intelligent' simulation tool with an embedded optimisation tool to solve various decision-making problems encountered during the simulation of a complex supply chain. Including an optimisation tool in a simulation tool allows accurate assessment of supply chains performances and overcome the lack of powers of decision-making in traditional simulation tools.