基于人工免疫的供应链风险管理仿真研究

发布时间：2018-08-21 10:50

【摘要】：供应链风险管理引起了越来越多的关注。通过有效管控风险来提高供应链系统的可靠性,和提高供应链的效率具有同样的重要意义。传统的基于还原论的研究方法如果仅仅关注少数变量之间的关系,不能有效解决供应链风险管理面对的不断变化的现实问题,有必要探讨基于整体论的供应链风险管理新思路。供应链系统抵抗供应链风险和生物免疫系统抗击病毒有许多相似之处。本文借鉴生物免疫系统构建了一个具有环境适应性的供应链风险管理模型。择优学习和组织记忆是基于人工免疫的供应链风险管理模型最核心的两部分内容。择优选择性学习为组织寻找最优解决风险事件的策略提供了空间。供应链依靠知识库的记忆机制不断的积累供应链风险管理经验,使得供应链风险管理水平随着运营时间不断增强。为了验证本文提出的供应链风险管理模型的有效性,我们借鉴March等提出的组织学习仿真模型,构建了一个基于人工免疫的供应链风险管理仿真模型。基于Netlogo平台使用多主体仿真技术进行仿真实验,结果表明供应链处理风险事件的速度随运营时间增加变短,供应链风险管理水平随运营时间增加逐步提高。另外,供应链企业风险管理知识共享和供应链风险事件演习可以有效的提高供应链风险管理的绩效。将人工免疫理论用于供应链风险管理,是在理论上的一次创新性的尝试。本文构建的基于人工免疫的供应链风险管理模型,从整体论的角度促进了供应链风险管理理论的发展,对企业建立面向供应链风险管理的知识管理系统也有一定的指导意义。
[Abstract]:Supply chain risk management has attracted more and more attention. It is of the same significance to improve the reliability of supply chain system through effective risk management and to improve the efficiency of supply chain. If the traditional research method based on reductionism only pays attention to the relationship between a few variables, it can not effectively solve the ever-changing realistic problems faced by supply chain risk management. Therefore, it is necessary to explore a new approach to supply chain risk management based on global theory. There are many similarities between the supply chain system resistance to supply chain risk and the biological immune system in fighting viruses. This paper constructs a supply chain risk management model with environmental adaptability for reference to biological immune system. Optimal learning and organizational memory are two core parts of supply chain risk management model based on artificial immune. Selective learning provides a space for an organization to find an optimal solution to risk events. Supply chain relies on memory mechanism of knowledge base to accumulate supply chain risk management experience, which makes supply chain risk management level increase with operation time. In order to verify the effectiveness of the supply chain risk management model proposed in this paper, a supply chain risk management simulation model based on artificial immune is constructed by using the organizational learning simulation model proposed by March et al. The simulation experiment based on Netlogo platform using multi-agent simulation technology shows that the speed of handling risk events in supply chain becomes shorter with the increase of operation time, and the risk management level of supply chain increases gradually with the increase of operation time. In addition, supply chain enterprise risk management knowledge sharing and supply chain risk event exercises can effectively improve the performance of supply chain risk management. It is an innovative attempt to apply artificial immune theory to supply chain risk management. The model of supply chain risk management based on artificial immunity, which promotes the development of supply chain risk management theory from the perspective of global theory, has some guiding significance for enterprises to establish knowledge management system for supply chain risk management.
【学位授予单位】：厦门大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F274;F224

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