双枝模糊评判在舰炮性能评估中的应用

针对舰炮武器性能指标,运用双枝模糊决策方法对舰炮武器性能进行综合评估。该方法提出了新的论域[-1,1]使评估更能符合人的思维逻辑,能够客观的对舰炮性能进行评估,通过对多中舰炮的具体参数指标进评估,得出各种舰炮的性能优劣的排序,具体的数学模型仿真表明,对舰炮武器性能的评估是行之有效的。     

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。     

基于模糊神经网络的反鱼雷深弹作战决策

反鱼雷深弹武器是水面舰艇对抗鱼雷的一种新的反鱼雷武器,由它组成的鱼雷防御系统可以拦截潜艇发射的声自导鱼雷、线导鱼雷及尾流自导鱼雷.根据其作战使用特点,建立基于模糊神经网络的智能辅助决策系统,分析了其基本思想,具体实现过程,并应用实例加以验证.计算结果表明:该模糊神经网络模型具有一定的合理性和实用性.     

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.     

无运力限制条件下的一种器材紧急调运优化模型

根据器材调运的特点建立了一个货量充足且无运力限制条件的多目标优化模型,给出了一种方便有效的算法,并利用仿真算例对模型和算法进行了验算,得到了最优的器材调运方案.     

机场目标打击顺序灰色决策分析

对军事机场目标的结构、特征进行了系统分析,确立了军事机场目标评估体系,并运用灰色决策分析方法建立了军事机场多目标打击顺序确定的优化模型,为对该类实施导弹打击所进行的火力计划拟制提供了一种新的数学方法。     

军区营房管理辅助决策信息系统设计研究

为满足现代战争对后勤保障提出的新要求,改革传统的营房保障模式,根据信息系统、数据库及网络建设的理论,通过对军区营房管理部门组织结构、工作流程、业务内容、部门权限的分析,提出了军区营房管理辅助决策信息系统设计的要求、系统的配置、系统主要模块划分等内容,为系统的进一步开发搭建了框架。     

基于贝叶斯决策的图像检索相关反馈方法研究

为了有效解决基于内容图像检索中“语义鸿沟”问题,利用贝叶斯决策理论估计图像检索中相关图像集与不相关图像集合的分类面,通过移动查询点的策略,指导新一轮的查询,将查询点移向好的范例点而远离坏的范例点。试验证明该方法是一种有效的基于统计分析的反馈方法。     

战役级军械维修器材保障决策支持系统设计研究

传统的面向事务的数据处理方法已经无法适应处理大量数据的要求,为解决这一问题,将面向主题的数据仓库技术用于军械维修器材保障决策支持系统的设计,阐述了基于数据仓库的军械维修器材保障决策支持系统需求分析、系统设计和系统实现,讨论了系统设计原则、设计方法、逻辑结构设计、多维数据仓库设计、底层数据库设计、前端用户视图设计等内容,对军械维修器材保障决策支持系统的开发提供了基本思路．