Logistics Flow Optimization for Advanced Management of the Crisis Situation

Abstract

Our work has been carried out with the aim of providing a solution to decision-making problems encountered in information systems for supply chains in crisis situation. The supply chain represents a competitive advantage that companies seek to perpetuate. It aims to optimize the exchanges, or flows, that the company maintains with its suppliers and its customers. These flows can be of various natures. It can be information flows relating to supplies or product design, financial flows linked to purchases, or even flows of goods. The crisis management logistics is getting more and more attention, especially in the current context of the COVID-19 pandemic. For these systems, where it is never very easy to anticipate the evolution of the environment, the forms of changes undergone are varied and rapid. We aim to provide an answer to these challenges, in an approach that links optimization methods to the paradigm of artificial intelligence. We therefore propose to find mathematical models, and inter-agent cooperation protocols, to minimize the risk of stock shortage in any area of ​​the supply chain.

Keywords: Crisis situation; Multiagent Systems; Supply Chain; logistics flow; modelisation; optimisation.