广东工业大学学报 ›› 2015, Vol. 32 ›› Issue (2): 43-47.doi: 10.3969/j.issn.1007-7162.2015.02.008

• 综合研究 • 上一篇    下一篇

跨组织间隐私数据水平分布线性规划协同优化算法研究

 陆涛, 刘洪伟, 刘智慧, 朱慧, 陈丽   

  1. 广东工业大学 管理学院,广东 广州 510520
  • 收稿日期:2014-11-18 出版日期:2015-05-30 发布日期:2015-05-30
  • 作者简介:陆涛(1988-),男,硕士研究生,主要研究方向为管理信息系统、电子商务.
  • 基金资助:

    国家自然科学基金资助项目(70971027);广东省普通高校人文社会科学重点研究项目(12ZS0112)

Collaborative Optimization Algorithm Research on Crossorganizations Privacy Data Horizontally Partitioned Linear Programing

Lu Tao, Liu Hong-wei, Liu Zhi-hui, Zhu Hui, Chen Li   

  1. School of Management,Guangdong University of Technology,Guangzhou 510520,China
  • Received:2014-11-18 Online:2015-05-30 Published:2015-05-30

摘要: 供应链协同优化决策中,在保护上下游成员私有信息的同时,得到全局的协同优化决策方案.利用安全多方计算的理论和基础协议,讨论在半诚实模型下具有线性结构的供应链协同优化算法,针对线性规划模型约束矩阵的信息水平分布与不同组织且目标函数也为隐私信息的情形,提出了基于随机矩阵变换的防推断的安全解决方法.该方法相对于传统的安全多方计算方法具有较高的计算效率.

关键词: 供应链管理; 协同优化; SMC; 水平分布

Abstract: This paper mainly studied how to obtain global optimal solutions to collaborative optimization decisionmaking in supply chain management under the premise of protecting the upstream and downstream members’s private information. By using secure multiparty computation theory and some basic protocols, this paper discussed the supply chain collaborative optimization algorithm for models with linear structure under the semihonest model and proposed an antiinfered approach to the linear programming model of which constraint matrix data is distributed in different parties by row and objective function is also another party’s privacy information. Compared with the traditional methods of secure multiparty computation, this algorithm has higher efficiency.

Key words: supply chain management; collaborative optimization; SMC; horizontally partitioned

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!