基于安全多方计算的产能约束供应商协同供货  

Suppliers synchronization replenishment under performance constraint based on secure multi-party computation

作　　者：李毅鹏[1,2] 马士华[1] 

机构地区：[1]华中科技大学管理学院,武汉430074 [2]中南财经政法大学信息与安全工程学院,武汉430073

出　　处：《控制与决策》2013年第11期1623-1629,共7页Control and Decision

基　　金：国家自然科学基金项目(71072035);国家863计划项目(2006AA04Z153)

摘　　要：针对供应链中核心制造商对产能约束的多个零部件供应商的"末位惩罚"问题,构建基于安全多方计算的多个供应商协同模型,并分析了分散决策和供应商协同决策下各个成员的最优决策.通过Monte Carlo模拟仿真方法和数例分析表明,采用基于安全多方计算的供应链信息共享机制,可在保护供应商的私有产能信息不公开的同时还能进行集中决策,从而明显降低供应商的损失成本和整个供应链的全局损失成本,最终让供应链达到帕累托改善.Focusing on the problem about ＂Last Penalty＂ taken by core manufacturer on components＇ suppliers constrained by performance in supply chain, a multi-suppliers＇ synchronization model based on secure multi-party computation is built. Considering two situations under independent decision and suppliers＇ joint decision, their optimal decision is analyzed respectively. Through the Monte Carlo simulation methodology and numerical example analysis, the results show that the information sharing mechanism in supply chain based on secure multi-party computation can take joint decision while protecting suppliers＇ private performance information undisclosed, and decrease the loss cost of suppliers and global loss cost of whole supply chain significantly, finally let the supply chain achieve Pareto improvement.

关 键 词：安全多方计算 供应商协同 产能约束 信息共享 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]