Contribution à la modélisation de la chaine logistique et son impact sur la performance des plateformes logistiques.

Abstract

The effective management of the supply chain has become crucial in today's business landscape to maintain companies' competitiveness. This thesis delves deep into the theoretical foundations, modeling methods, performance evaluation, and practical applications, with a particular focus on distribution networks. Initially, we lay out the theoretical underpinnings of logistics and supply chain management, covering essential definitions and concepts, including stakeholders, flows, processes, and the notion of supply chain management. Subsequently, we explore specific aspects of logistics services, warehouses, logistics platforms, and distribution networks. Following that, we delve into the state-of-the-art in modeling and evaluating supply chain performance, presenting various approaches and methodologies. We start with organizational models, which provide a static but fundamental view of the structure and functioning of the supply chain, and then deepen our analysis by exploring dynamic modeling techniques, including analytical and simulation models. We also pay special attention to performance evaluation, reviewing various approaches such as the ABC – ABM method, the Balanced ScoreCard (BSC), the SCOR model, and other frameworks. An adaptation of the SCOR model is then proposed to evaluate the performance of Numiog's logistics platforms, with a detailed analysis of logistics processes, identification of key performance indicators, and recommendations for best practices to enhance operational efficiency. Additionally, the use of the SCOR model has enabled Numilog to standardize its processes and compare its performance against industry standards. We also observe an emerging trend in the scientific literature, with a significant increase in publications focusing on modeling and simulating supply chains using multi-agent systems, particularly with software like AnyLogic. A case study presents the use of AnyLogic to model and simulate Cevital's agri-food product distribution network, focusing on agentbased and discrete-event modeling. By leveraging AnyLogic's capabilities, we developed a realistic simulation model to determine the optimal number of vehicles needed to meet customer demands while maintaining efficient fleet utilization. Finally, we emphasize the importance of simulating the logistics chain, especially with tools like AnyLogistix. A specific case study was conducted to assist Cevital's decision-makers in determining the location of new logistics platforms and the optimal number of sites to open, by examining the impact of strategically distributing platforms on the overall performance of the logistics chain. The in-depth analysis of Cevital's distribution network in Algeria, conducted using Green Field Analysis (GFA) and simulations with AnyLogistix to model real-time delivery with detailed Key Performance Indicators (KPIs), has highlighted that strategically adding two new logistics platforms in Sétif and Rélizane resulted in a significant reduction in traveled distances, suggesting potential cost savings. The simulations allowed for the evaluation of various GFA scenarios, identifying Scenario 3 as the optimal choice to enhance Cevital's performance. This scenario effectively balances reducing CO2 emissions, decreasing transport costs, and optimizing the number of vehicles used, thereby providing a solid foundation for informed strategic decisions and enabling anticipation of potential impacts of proposed changes before their implementation.