系统仿真学报 ›› 2021, Vol. 33 ›› Issue (11): 2720-2732.doi: 10.16182/j.issn1004731x.joss.21-FZ0664E

• 仿真模型/系统置信度评估技术 • 上一篇    下一篇

基于供应商画像与马尔可夫蒙特卡罗仿真的供应商选择

孙炳利1, 宋晓2, 龚光红1   

  1. 1.北京航空航天大学 自动化科学与电气工程学院,北京 100191;
    2.北京航空航天大学 网络空间安全学院,北京 100191
  • 收稿日期:2021-06-13 修回日期:2021-07-13 出版日期:2021-11-18 发布日期:2021-11-17

Supplier Selection Based on Supplier Portrait and Markov Monte Carlo Method

Sun Bingli1, Song Xiao2, Gong Guanghong1   

  1. 1. School of Automation Science & Electrical Engineering, Beihang University, Beijing 100191, China;
    2. School of Cyber Science & Technology, Beihang University, Beijing 100191, China
  • Received:2021-06-13 Revised:2021-07-13 Online:2021-11-18 Published:2021-11-17
  • Contact: Song Xiao (1976-), male, PhD, associate professor, research area: intelligent manufacturing and simulation. E-mail: songxiao@buaa.edu.cn
  • About author:Sun Bingli(1997-), male, master student, research area: intelligent manufacturing and simulation. E-mail: youthbl@163.com
  • Supported by:
    Key R&D Projects (2020YFB1712203)

摘要: 供应商选择是一个复杂的多目标决策问题,建立供应商的画像角度是关键所在。面向航天装备领域的供应商选择,综合考虑企业资质管理、经营风险、产品质量对其进行画像,基于贝叶斯理论对画像样本数据实现了多参数联合分布推导。结合推导出的数学模型,提出了一种马尔可夫蒙特卡洛仿真方法,结合吉布斯采样器在数据难以获取或缺失的情况下实现了供应商排名和选择,为航天领域供应商选择提供了一种新的思路。

关键词: 供应商画像, 马尔可夫蒙特卡罗法, 吉布斯采样, 贝叶斯理论, 供应商选择

Abstract: The supplier selection problem is a complex multi-objective decision-making problem and the key is how to establish the supplier's portrait. For the supplier selection of aerospace equipment, enterprise qualification management, business risks, and product quality are comprehensively considered. Based on Bayesian theory, the multi-parameter joint distribution derivation of portrait sample data is realized. Combined with the mathematical model derived, a Markov Monte Carlo simulation method is proposed. And combined with Gibbs sampler, the supplier ranking and selection are achieved when data is difficult to obtain or missing, which provides a new idea for supplier selection in the aerospace field.

Key words: supplier portrait, Markov Monte Carlo Method, gibbs sampling, bayesian theory, supplier selection

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