Generic framework for logistics planning in a context of centralized and distributed decisions.

Summary This thesis recalls the fundamentals of logistics systems management and shows the interest of setting up a PCS (Product Controlled System). The integration of such systems must first take into account the coherence between the different elements that constitute it. Thus, centralized systems try to propose medium-long term plans aiming at an optimal cost, but also a certain stability and little nervousness in time. On the other hand, distributed systems have demonstrated their capacity to allow a rapid reaction to impromptu events occurring in the physical system. The hybridization of these two types of control is therefore a way to gain productivity for logistic and industrial systems. The first chapter of the thesis describes the evolution of production planning and control systems, with the objective of identifying the strengths and weaknesses of the different approaches proposed up to now and to define the general objective of the thesis. Chapter two analyzes the state of the art concerning the modeling tools for centralized/distributed production systems and also the concept of product control. This chapter serves as a basis for defining the specific objectives of the thesis. Chapter three presents the proposed modeling framework. This framework is based on a cybernetic approach, and more specifically on the viable system model (VSM). The chapter starts with a general presentation of the viable system model, then presents a generic model for modeling product-controlled systems. Finally, the chapter describes an application of this general framework to PCS-type production planning and control systems. Chapter four defines the different decision methods, both centralized and distributed, developed for the implementation of the generic model defined in chapter three. At the centralized and distributed levels these methods are based on mathematical programming models developed to consider the adaptability and flexibility of the system. Chapter five shows the main results in an application based on an industrial case that required the development of a simulation tool that considers short, medium and long term variables for the different optimization models. These results show the interest of this type of hybridization.