Chakir Imane, El Khaili Mohamed, Mestari Mohamed
Laboratory SSDIA, ENSET Mohammedia, Hassan II University of Casablanca, BP. 159, Mohammedia, Morocco.
Procedia Comput Sci. 2020;175:419-426. doi: 10.1016/j.procs.2020.07.059. Epub 2020 Aug 6.
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.
我们开展这项工作的目的是为危机情况下供应链信息系统中遇到的决策问题提供解决方案。供应链是公司力求保持的竞争优势。它旨在优化公司与其供应商和客户之间的交换或流动。这些流动可以具有各种性质。它可以是与供应或产品设计相关的信息流、与采购相关的资金流，甚至是货物流。危机管理物流越来越受到关注，尤其是在当前新冠疫情的背景下。对于这些系统，由于很难预测环境的演变，所经历的变化形式多样且迅速。我们旨在通过将优化方法与人工智能范式相结合的方法来应对这些挑战。因此，我们建议找到数学模型和智能体间合作协议，以最大限度地降低供应链任何领域出现库存短缺的风险。
