基于信息优势的决策能力分析

随着信息优势评估的不断深入,信息优势支持下的决策优势能力,已成为C4ISR系统作战效能评估的又一重要研究内容.从决策优势的基本概念入手,通过分析决策优势与信息优势的关系,提出了决策周期时间、决策质量和决策循环速度三个衡量决策优势的基本度量,并结合典型作战样式和信息优势的准确性、完备性指标,分析了这些度量的基本构成和量化方法.通过兰彻斯特方程,导出了一种可用于仿真评估的决策优势能力量化公式,进而指明了夺取决策优势应采取的主要措施.     

预警机指挥多机群空战的协同战术决策

分析了预警机指挥下的多机群协同空战的战术决策方法,建立起了它的战术编队、威胁评估以及目标分配模型,并进行了仿真计算,结果表明此战术决策方法对于提高多机群协同空战的作战效能有着显著的作用,对于未来无人作战飞机多编队协同作战也具有很好的参考价值.     

战役野战油库油料输送力量优化分配研究

如何科学、合理分配战役野战油库油料输送力量是战时油料保障必须面临的一个实际问题。首先根据战役野战油库运油车分配模型得到一个运油车初始分配方案,然后运用计算机模拟技术对分配方案进行模拟,并根据模拟结果不断调整,直至得到优化的分配方案,为制定战役野战油库油料输送计划提供决策依据。     

Optimal production ramp-up in the smartphone manufacturing industry

Motivated by challenges in the smartphone manufacturing industry, we develop a dynamic production ramp-up model that can be applied to economically satisfy nonstationary demand for short-life-cycle products by high-tech companies. Due to shorter life cycles and more rapid evolution of smartphones, production ramp-up has been increasingly critical to the success of a new smartphone. In the production ramp-up, the key challenge is to match the increasing capacity to nonstationary demand. The high-tech smartphone manufacturers are urged to jointly consider the effect of increasing capacity and decreasing demand. We study the production planning problem using a high-dimensional Markov decision process (MDP) model to characterize the production ramp-up. To address the curse of dimensionality, we refine Monte Carlo tree search (MCTS) algorithm and theoretically analyze its convergence and computational complexity. In a real case study, we find that the MDP model achieves revenue improvement by stopping producing the existing product earlier than the benchmark policy. In synthetic instances, we validate that the proposed MCTS algorithm saves computation time without loss of solution quality compared with traditional value iteration algorithm. As part of the Lenovo production solution, our MDP model enables high-tech smartphone manufacturers to better plan the production ramp-up.     

Revenue maximization in two-station tandem queueing systems

We study optimal pricing for tandem queueing systems with finite buffers. The service provider dynamically quotes prices to incoming price sensitive customers to maximize the long-run average revenue. We present a Markov decision process model for the optimization problem. For systems with two stations, general-sized buffers, and two or more prices, we describe the structure of the optimal dynamic pricing policy and develop tailored policy iteration algorithms to find an optimal pricing policy. For systems with two stations but no intermediate buffer, we characterize conditions under which quoting either a high or a low price to all customers is optimal and provide an easy-to-implement algorithm to solve the problem. Numerical experiments are conducted to compare the developed algorithms with the regular policy iteration algorithm. The work also discusses possible extensions of the obtained results to both three-station systems and two-station systems with price and congestion sensitive customers using numerical analysis.     

基于NSGA-Ⅱ的WTA多目标优化(英文)

将多目标遗传算法NSGA-(改进的非支配排序遗传算法)应用于求解武器-目标分配(WTA)问题。首先,针对以往在建立防空型WTA问题的优化模型上的片面性,把WTA问题看做多目标优化问题,建立了综合考虑作战效能和防御效能的WTA双目标优化模型。然后在此基础上,研究和应用了NSGA-来求解WTA问题。最后由仿真算例验证了NSGA-在WTA问题中的应用可行性,表明了NSGA-可以快速地搜索到WTA多目标优化的Pareto最优解集,从而为求解WTA问题提供了一条有效途径。     

一种基于协调理论的军事决策过程建模方法

在分析协调理论应用的基础上,针对军事决策过程的建模,基于UML2.0的用例图,提出了基于协调理论的军事决策过程建模方法。应用该建模方法,有利于分析军事决策过程中的核心任务活动及其相关依赖,为指挥员实施平行决策,并发地制订和确定作战方案(Course of Action)提供依据,从而提高军事决策过程的适应性。     

大连7·16油罐区爆炸火灾事故成功处置的启示

随着我国石油化工工业的发展以及国家原油战略储备库项目的实施,油罐的大型化已成为发展的必然趋势,现在10万m3的储罐已经屡见不鲜。如此巨大的油罐一旦发生火灾爆炸,其后果是难以想象的。2010年7月16日发生的大连中石油国际储运有限公司保税区油库爆炸火灾的成功处置最大限度的保护了国家财产,最大限度地减少了其对生态环境的破坏,笔者全程参与了此次事故处置指挥,力求通过总结这次作战行动,侧重从特大石化爆炸火灾事故组织指挥层面提供可供借鉴的经验做法。     

基于风险评估的检测与修理决策模型

研究了基于故障风险的检测与维修策略,运用威布尔比例风险模型建立系统故障率与工作时间及所处状态的关系。分析了两类基于间接状态信息维修决策的风险,建立了系统检测及维修策略的决策树,通过比较检测与不检测情况下的期望费用确定最优的检测间隔。算例表明,所提出的方法能够有效控制系统运行风险,降低系统运行费用。     

基于遗传模拟退火算法的OFDMA系统资源分配

针对多用户OFDMA系统,提出了一种基于遗传模拟退火算法的多用户OFDMA系统资源分配策略。在资源分配时,首先假设总功率在载波间均等分配,随后根据比例速率要求确定每个用户需要的子带数,最后引入遗传模拟退火算法求解联合优化中的子带分配,在保证用户间公平性的前提下最大化系统吞吐量。仿真结果表明,该策略系统容量较大,并且近似满足了不同用户间传输速率比例性要求。