In the recent decades, many external factors (e. G. Natural disasters, terrorist attacks, and political turmoil) have constantly disrupted the normal operations of some large-scaled systems, such as power grids, communication stations and chemical plants. The system disruption can cause great losses to a society and its economy. The management begins paying attention to hedging risks of system disruptions. Current literature underestimates the potential influence of a decision maker's risk attitude ( e. G. Risk-netural, conservative or aggressive) on risk management. To provide a reasonable model to manage risks associated with the capacity disruption, we add the risk attitude of decision makers to a mathematical model.In the year of 2008, a great freezingA heavy rain hit the southern China in 2008 and, which caused the a wide-ranged collapse of power grids. When managing the disruption, we found that damaged systems need to face two important issues. First, During the disruption management, we found two interesting restricts that capacity-injured systems have to face; first, the recovery of critical capacity is a cost-expensive and multi-periods process, due to the technique of maintenance department and provision of spare parts.Second, capacity-sharing partners could support parts of capacity that is usually much cheaper than recovery; however, the sharing of capacity has limited quantity and uncertain provision. Based on these findings, a a factor is firstly constructed to map the inventory and capacity-shortage into a decision-maker's risk attitude. Second, we proposed a single-period capacity disruption management model and then extended it to a multi-period model that has a proven unique solution sequence. Finally, we present a sensitive analysis towards key parameters by using the Genetic Algorithm.A comparison is presented with the research of [ 17 ] , we find 4Four interesting managerial insights were discovered. First, aggressive or conservative of decision-maker's risk attitude of decision makers s merely have has no influence towards on the disruption cost but complicates the decision. This finding, which means that the decision makers should need higher computation ability during the disruption management. Second, the quantity of shared capacity also merely has no influence on the disruption cost either.In fact, production operation system could greatly lower the cost no matter how much support the capacity-sharing partner could provide during the disruption management. Third, high recovery ability of maintenance contributes greatly to the disruption cost, but decrease the marginal benefit. Finally, we reach the conclusion that shortening or prolonging the time of disruption seems to have no influence on disruption cost due to the existence of capacity supporting. Decision makers could have more flexibility to deal with different emergent situations.%分析了生产运作系统能力的应急管理模式,围绕应急期间系统内部能力恢复和外部能力采购以及管理者风险态度的影响,以应急总成本最小为目标构建了能力应急管理模型,并对该多阶段应急模型进行数值分析后得到4个重要的应急管理结论,对管理者制定科学的应急决策均具有重要的指导意义.
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