Resilient supply chain design : a new framework to mitigate unknown unknown disruption risk through redundancy and flexibility

This work of thesis is developed in the field of Supply Chain Risk Management. The objective of the study is twofold. The first part will provide a deep analysis of the works present in literature which deal with mathematical programming tools to manage disruptions in supply chain. A well-structured classification will be provided and will be the basis on which a clusterization will be done. This tool will be useful to drive scholars in the research of models that have been already published in literature; thanks to the identification of certain key variables, they will be easily able to find the models which are aligned with their necessities. The second section of the thesis will describe the development of a framework methodology to support managers in decision taking when designing a resilient supply chain. The analysis of a real case study drove us to the development of this new tool since no one among the analyzed models was satisfying to solve the problem. The proposed framework methodology is composed of more steps in which optimization algorithms, simulations and heuristics are used together to drive the decision maker to the best solution according to his necessities. The strength of this tool is due to its possibility to be customized in accordance to the context peculiarity and to the decision maker’s needs and to the fact that can be used in unknown unknown conditions. That is to say Risk Management process in supply chain design phase can be carried out without occurrence probability estimation.