Tactical production planning for physical and financial flows of supply chain in a multi-site context

Abstract

AcknowledgementFirst and foremost, I would like to express my sincere gratitude to my supervisors, Prof. Nathalie BOSTEL, David LEMOINE and Thomas YEUNG for all their contributions of time, ideas, and funding to make my Ph.D. experience productive and stimulating. Their continuous support, advice, caring, and trust throughout the past three and a half years was contagious and motivational for me, even during tough times in the Ph.D. pursuit. During my master internship and my Ph.D. program, I have benefited enormously from their valuable comments, their innovative approaches and serious attitude regarding research. I am also thankful for the excellent example they have provided as a researcher in Operations recherches that will guide and encourage me for my future career.Special thanks goes to Prof. Safia KEDAD-SIDHOUM (Université Pierre Marie CURIE (Paris 6)), who teached me during my master program, supervised my master internship and whom became one of my thesis reviewers. Also a thank-you to Prof. Stefan HELBER (Leibniz Universität Hannover) for being part of my Generals committee, a thesis reviewer, and who provides many profound advises during an international workshop. And thank you to Prof. Pierre FENIES (Université Paris Ouest Nanterre La Défense) for his insightful comments from a financial point of view after reviewing my thesis. I am also grateful to other members of the defense committee, Prof. Alexandre DOLGUI (IMT Atlantique) and Prof. Jean-Laurent VIVIANI (Université de Rennes 1) for letting my defense be an enjoyable moment, and for your brilliant comments and suggestions that inspired me in many ways.Our research works took part of the project RCSM which is financed by the French Competitiveness Cluster. In the context of this project, the collaboration with Prof. Jean-Laurent VIVIANI and Prof. Vincent HOVELAQUE (IGR-IAE of Rennes I) made our works possible and ensured its financial coherence with their knowledge and expertise in finance. I am grateful for all comments, advises and suggestions that I received for this thesis and I hope many success for the following project on this topic.During the stay at IMT Altantique, the members of the team SLP of LS2N have contributed immensely to my personal and professional time. The team has been a source of friendships as well as good advice and collaboration. I would like to thank Fabien LEHUEDE, Prof. Olivier PETON, Odile MORINEAU, Naly RAKOTO, Guillaume MASSONNET, Laurent TRUFFET, Chams LAHLOU, Nadjib BRAHIMI for their helps, constructive discussions and considerations for the conviviality in the laboratory and to improve my research works. I am especially grateful to Axel GRIMAULT and Fabrice GAYRAUD who were always willing to provide their kind helps with my research and with my daily life. My gratitude also goes to

A robust fuzzy-stochastic optimization model for managing open innovation uncertainty in the ambidextrous supply chain planning problem

“…This study identified two FSCM sets namely 1) pre-shipment FSCM and 2) postshipment FSCM to improve upstream and downstream supply chain working capital, respectively. A limited number of research works focused on integrated physical-financial planning models (see Vafa Arani and Torabi, 2018;Silvestro and Lustrato, 2014;Bian, 2017).…”

“…Furthermore, to develop a supply chain tactical planning according to financial and physical purposes, Bian (2017) As the literature shows, the optimization of physical flow has received more attention than the financial flow between the different supply chain partners. However, to enhance the cash flow predictability, decrease the risk-related costs, and enhance the working capital and cash flows, supply chain managers are willing to engage novel approaches for managing financial flows throughout the supply chain.…”

A Meta Model for a Blockchain-based Supply Chain Traceability

“…). The informational flow represents exchanges of data between supply chain actors or indicates activities' status [32]. Among the information to trace, it is possible to distinguish three main traceability data types: Master Data, Events and Transactional (See " Fig.…”