Two novel critical shock models based on Markov renewal processes

In this paper, we investigate systems subject to random shocks that are classified into critical and noncritical categories, and develop two novel critical shock models. Classical extreme shock models and run shock models are special cases of our developed models. The system fails when the total number of critical shocks reaches a predetermined threshold, or when the system stays in an environment that induces critical shocks for a preset threshold time, corresponding to failure mechanisms of the developed two critical shock models respectively. Markov renewal processes are employed to capture the magnitude and interarrival time dependency of environment-induced shocks. Explicit formulas for systems under the two critical shock models are derived, including the reliability function, the mean time to failure and so on. Furthermore, the two critical shock models are extended to the random threshold case and the integrated case where formulas of the reliability indexes of the systems are provided. Finally, a case study of a lithium-ion battery system is conducted to illustrate the proposed models and the obtained results.     

Newsvendor problems with sequentially revealed demand information

This article analyzes a capacity/inventory planning problem with a one‐time uncertain demand. There is a long procurement leadtime, but as some partial demand information is revealed, the firm is allowed to cancel some of the original capacity reservation at a certain fee or sell off some inventory at a lower price. The problem can be viewed as a generalization of the classic newsvendor problem and can be found in many applications. One key observation of the analysis is that the dynamic programming formulation of the problem is closely related to a recursion that arises in the study of a far more complex system, a series inventory system with stochastic demand over an infinite horizon. Using this equivalence, we characterize the optimal policy and assess the value of the additional demand information. We also extend the analysis to a richer model of information. Here, demand is driven by an underlying Markov process, representing economic conditions, weather, market competition, and other environmental factors. Interestingly, under this more general model, the connection to the series inventory system is different. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 2012     

马尔可夫过程的k/N系统使用任务完成能力分析

研究了任务期间允许换件维修和备件供应时k/N系统的任务完成能力.首先,利用马尔可夫过程分析了k/N系统的状态转移过程,研究了k/N系统在特定维修保障策略下的运行过程.然后,以k/N系统固定任务时间内在正常状态停留时间的分布函数作为其任务完成概率模型,并通过全概率分解和更新过程的分析方法对任务完成概率进行求解.最后,利用任务完成概率模型在Matlab中绘制了任务完成概率随任务时间、任务量、备件携行数量以及备件平均供应时间的变化曲线,讨论并分析了对任务完成概率的影响.     

不完备检测下视情维修的多级劣化系统性能评估

视情维修是改善多级劣化系统性能表现的重要措施,然而在实际中检测不完备问题会制约视情维修的有效开展,从而影响劣化系统性能评估结果。针对这一问题,将多级劣化系统检测维修马尔科夫链模型中的状态转移进行调整,建立其在不完备检测下进行视情维修的性能评估模型,给出系统性能参数的求解方法。实例验证表明:在实际工作中,虚警和漏检对于系统瞬态可用度的影响是随时间变化而不定的,但对于系统可靠度的影响则是确定的,即在任意时刻虚警提高系统可靠度,而漏检降低系统可靠度。     

基于推理的体系对抗条件下空袭目标优选方法

针对体系对抗条件下空袭目标选择缺乏不确定多要素分析能力和足够的自主推理能力,研究了空袭体系的基本作战样式,根据智能决策模拟系统需求,结合决策行为产生机理,建立基于区间数的综合推理模型,给出空袭目标优选规则,提出基于推理的体系对抗条件下空袭目标优选方法,最后给出一个仿真实例。实例结果表明,该方法可作为体系对抗条件下作战仿真系统的重要组成部分,为军事指挥员提供辅助决策支持。