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. Aiming at the problem of “last punishment ” of multiple suppliers in the supply chain, which is constrained by the production capacity, a multi-supplier collaborative model based on secure multi-party calculation is constructed and the decentralized decision-making and supplier collaborative decision-making are analyzed. The optimal decision-making of each member.According to the Monte Carlo simulation method and the numerical analysis, it is shown that the information sharing mechanism of supply chain based on secure multi-party computing can make centralized decision-making while protecting the private capacity information of suppliers. , Thereby significantly reducing the cost of suppliers’ losses and the global loss cost of the entire supply chain, eventually leading to Pareto improvement in the supply chain.