东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (9): 1241-1244.DOI: -

• 论著 • 上一篇    下一篇

基于随机规划和遗传算法的虚拟企业风险管理

卢福强;黄敏;王兴伟;   

  1. 东北大学信息科学与工程学院;东北大学流程工业综合自动化教育部重点实验室;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-09-15 发布日期:2013-06-22
  • 通讯作者: Lu, F.-Q.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(70671020,70431003,60673159);;

Risk management of virtual enterprise based on stochastic programming and GA

Lu, Fu-Qiang (1); Huang, Min (1); Wang, Xing-Wei (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China; (2) Key Laboratory of Integrated Automation of Process Industry, Ministry of Education, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-09-15 Published:2013-06-22
  • Contact: Lu, F.-Q.
  • About author:-
  • Supported by:
    -

摘要: 针对虚拟企业的风险因素具有随机性的特点,将随机风险因素描述为随机变量,提出了一个虚拟企业风险管理的随机规划模型.针对该模型设计了嵌入蒙特卡罗模拟的遗传算法,蒙特卡罗模拟是处理模型中随机变量的有效方法.仿真分析表明了该算法的有效性和该随机规划模型对于虚拟企业风险管理的重要作用.

关键词: 虚拟企业, 风险管理, 随机规划, 遗传算法, 蒙特卡罗模拟

Abstract: The main feature of risk factor in a virtual enterprise (VE) is stochastic, and a stochastic risk factor can be regarded as a stochastic variable with which a stochastic programming model is developed for risk management of VE. To solve the stochastic programming model, a Monte Carlo simulation is combined in genetic algorithm (MCS-GA) since the Monte Carlo simulation is a very effective method to deal with stochastic variables. The simulation analysis is given to illustrate the effectiveness of the MCS-GA, and the proposed model is verified to be an important role to play in the VE.

中图分类号: