A Multi-agent Supply Chain Simulation Analysis through a Statistical Mixed Model

Supply chain coordination is a problem that arises in a supply chain and it is necessary to understand and analyse it as a set of dependencies both in physical flows, as well as in informational flows. The need to manage these dependencies is important for a company's success. In this paper, data from a supply chain simulation model, which is based on the multi-agent system simulation approach, was considered. A pharmaceutical case study was used to help and explore various coordination mechanisms, under different operational conditions. These scenarios were previously proposed and presented in the work of Vieira [9], and it becomes necessary to analyse and choose the best procedure to coordinate the supply chain, which will be done using a statistical model. In each scenario, data reveal within-group correlation and statistical mixed models are a flexible way to model this dependence, and, therefore, are used in this case study and presented in this paper.