大型复杂装备研制项目群风险管理研究

为有效避免研制项目出现"拖、降、涨"等恶性现象,大型复杂装备研制多采用项目群管理模式,由于同时开放了风险环境,增强了子项目间的复杂交互,使得研制项目群风险管理成为制约项目研制成功率的关键因素。目前装备研制风险管理研究以及项目群风险管理研究多是从静态或局部的角度来展开,虽然也有数值仿真方面的研究,但是对不同风险因素间的动态交互行为,及其进而造成的风险动态演化机制缺乏系统的分析,于是项目群风险演化动力学问题成为下一步的重要研究方向。     

对装甲旅（团）专业技术人才队伍建设的几点思考

人才是战斗力生成的关键之所在.装甲旅(团)是我军作战与编制的实体,装备保障专业技术人才培养与管理至关重要.装甲旅(团)必须盘活用人视角,把握人才成长的内外因素和一般规律,科学筹划专业人才发展战略,促进专业技术人才队伍不断发展壮大,以适应两个根本性转变的要求,迎接世界新军事技术革命的挑战.     

空降作战实验技术框架

开展空降作战领域新思想、新概念、新方案、新技术的实验研究,在实验室设计"未来战争",是开拓认识、驾驭、赢得信息化条件下空降作战广阔空间的有效途径。探讨了空降作战实验的内涵,提出了空降作战实验设计的总体技术结构框架。在此基础上,重点研究了空降作战实验的模型体系结构,并对空降作战实验应用系统的体系结构设计进行了深入分析,旨在为空降作战实验的顶层设计研究及具体实现提供参考。     

【专题】人工智能装备质量监督效能研究

近年来,人工智能技术迅速发展和渐趋成熟,在装备领域的应用大放异彩,极大地拓展了传统装备性能,特别是自主性和智能化水平。但人工智能算法本身固有的逻辑推理性差、具有不可解释性和需要学习训练等特性给人工智能装备的质量监督带来了新挑战,现有评价手段的欠缺也使人工智能装备发展在实用可靠方面充满不确定性。本文在总结归纳人工智能装备新特性拓展和质量监督新挑战的基础上,重点围绕有效提升人工智能装备的质量监督展开研究。提出应在夯实基础能力设施建设、注重日常数据采集整理、灵活技术状态管控、研究有效评价手段、强化人才队伍建设和闭环质量信息反馈与利用等六方面加强人工智能装备质量监督的措施建议,以期为人工智能装备的发展建设提供参考。     

高技术条件下的装备保障

通过分析研究高技术条件下装备保障的特点,概要阐述了外军装备保障的发展趋势,重点分析了我军装备保障的现状和发展中存在的问题,提出了装备保障发展的建设性意见.     

乙二醇生产火灾危险性及工艺防火对策

介绍了乙二醇生产工艺流程,分析其生产过程中的火灾危险性,并从工艺角度提出防火对策.     

前苏联发展反卫星武器的回顾

随着军用卫星的种类变化和性能提高 ,以及为谋求外层空间作战的军事优势 ,前苏联一直在积极发展反卫星武器。介绍了前苏联反卫星武器的组成、特点、技术方案及其发展情况 ,最后归纳了关于前苏联反卫星武器的几点看法。     

The LP/POMDP marriage: Optimization with imperfect information

A new technique for solving large‐scale allocation problems with partially observable states and constrained action and observation resources is introduced. The technique uses a master linear program (LP) to determine allocations among a set of control policies, and uses partially observable Markov decision processes (POMDPs) to determine improving policies using dual prices from the master LP. An application is made to a military problem where aircraft attack targets in a sequence of stages, with information acquired in one stage being used to plan attacks in the next. © 2000 John Wiley & Sons, Inc., Naval Research Logistics 47: 607–619, 2000     

Mathematical formulation and heuristic algorithm for the block relocation and loading problem

This study considers the block relocation and loading problem in container terminals. The optimal loading sequence and relocation location are simultaneously decided on the basis of the desired ship‐bay and initial yard space configuration. An integer linear programming model is developed to minimize the number of relocations in the yard space on the basis of no shifts in the ship bay. The accuracy of the model is tested on small‐scale scenarios by using CPLEX. Considering the problem size in the real world, we present a rule‐based heuristic method that is combined with a mathematical model for the removal, loading, and relocation operations. The influence of rules on algorithm performance is also analyzed, and the heuristic algorithm is compared with different types of algorithms in the literature. The extensive numerical experiments show the efficiency of the proposed heuristic algorithm.     

On the reduction of total‐cost and average‐cost MDPs to discounted MDPs

This article provides conditions under which total‐cost and average‐cost Markov decision processes (MDPs) can be reduced to discounted ones. Results are given for transient total‐cost MDPs with transition rates whose values may be greater than one, as well as for average‐cost MDPs with transition probabilities satisfying the condition that there is a state such that the expected time to reach it is uniformly bounded for all initial states and stationary policies. In particular, these reductions imply sufficient conditions for the validity of optimality equations and the existence of stationary optimal policies for MDPs with undiscounted total cost and average‐cost criteria. When the state and action sets are finite, these reductions lead to linear programming formulations and complexity estimates for MDPs under the aforementioned criteria.© 2017 Wiley Periodicals, Inc. Naval Research Logistics 66:38–56, 2019