策略不确定条件下基于高阶超博弈的军事对抗决策方法

军事对抗决策中面临的一个主要问题是难以确定敌方的策略集。基于超博弈分析策略不确定条件下的军事对抗决策问题。在分析超博弈中信念迭代原理的基础上,提出了基于高阶超博弈的对抗决策方法。将高阶信念中的结果反思到低阶信念,并最终反思到一阶信念中,将己方的决策建立在对敌方可能决策的分析的基础上。使得己方的决策具有针对性且更加合理。以二战中西线战役为例验证了方法的可行性和有效性。     

返回器飞行管道的快速预测算法

针对返回器回收任务中对安全空域和期望落点的计算需求,提出了基于Koopman算子的飞行管道快速预测算法,给出了搜救直升机安全飞行空域的判定流程。建立了物伞动力学模型,利用Halton采样方法从随机空间中均匀采点,计算得到多条可能弹道;采用Koopman算子的后拉机制,将初始概率密度值与当前状态关联,得到不确定条件下返回器及其分离部件的飞行管道和期望弹道。仿真结果表明,基于Koopman算子的飞行管道快速预测算法在收敛速度和精度上都要显著优于Monte Carlo方法;利用飞行管道计算结果对搜救直升机飞行路线进行规划后,碰撞风险最大降低54%且搜索时间减少70%。飞行管道预测算法已成功应用到嫦娥五号的回收任务中。     

随机-区间混合不确定性单输出模型确认指标

针对既有随机变量又有区间变量的模型预测结果与实验数据之间的一致性度量问题,对随机-区间混合不确定性模型确认指标进行研究。根据工程数学模型和实验过程中的不确定性来源,分析随机-区间混合不确定性模型确认的特点;运用概率方法和区间理论,提出新的随机-区间混合不确定性模型确认指标,讨论所提指标的性质,给出指标的计算方法和步骤。通过数字算例和工程算例,验证了所提指标的可行性和有效性。     

A guarantee rate optimization model for wastewater treatment system design under uncertainty

We consider a design problem for wastewater treatment systems that considers uncertainty in pollutant concentration levels at water sources. The goal is to optimize the selection of treatment technologies and pipeline connections, so that treated wastewater can achieve specified effluents discharge limits as well as possible. We propose a new two-stage model to optimize a set of guarantee levels, that is, the maximum concentration level of source pollutants for which treated wastewater can be compliant with discharge limits. In the first stage, treatment technologies and pipeline connections are selected. In the second stage, when pollutant concentration levels are revealed, wastewater distribution and mixing are determined. A key attractiveness of the proposed guarantee rate optimization model is that it can be simplified into a single-stage mixed-integer linear program. In our numerical experiments based on real-world pollutants data, the guarantee rate model demonstrates its advantages in terms of computational efficiency, scalability and solution quality, compared with the standard probability maximization model. Finally, the methodology proposed in this paper can also be applied to other two-stage problems under uncertainty with similar uncertainty characteristics.     

Flexible capacity strategy in an asymmetric oligopoly market with competition and demand uncertainty

This article studies flexible capacity strategy (FCS) under oligopoly competition with uncertain demand. Each firm utilizes either the FCS or inflexible capacity strategy (IFCS). Flexible firms can postpone their productions until observing the actual demand, whereas inflexible firms cannot. We formulate a new asymmetrical oligopoly model for the problem, and obtain capacity and production decisions of the firms at Nash equilibrium. It is interesting to verify that cross‐group competition determines the capacity allocation between the two groups of firms, while intergroup competition determines the market share within each group. Moreover, we show that the two strategies coexist among firms only when cost differentiation is medium. Counterintuitively, flexible firms benefit from increasing production cost when the inflexible competition intensity is sufficiently high. This is because of retreat of inflexible firms, flexibility effect, and the corresponding high price. We identify conditions under which FCS is superior than IFCS. We also demonstrate that flexible firms benefit from increasing demand uncertainty. However, when demand variance is not very large, flexible firms may be disadvantaged. We further investigate the effects of cross‐group and intergroup competition on individual performance of the firms. We show that as flexible competition intensity increases, inflexible firms are mainly affected by the cross‐group competition first and then by the intergroup competition, whereas flexible firms are mainly affected by the intergroup competition. Finally, we examine endogenous flexibility and identify its three drivers: cost parameters, cross‐group competition, and intergroup competition. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 117–138, 2017     

时间跨度对GPS坐标序列噪声模型及速度估计影响分析

选取全球范围内72个基准站的坐标序列,采用改进的赤池信息量准则、贝叶斯信息量准则对不同噪声模型组合进行噪声分析,得到基准站坐标序列的最优噪声模型及速度参数,探讨时间序列跨度对噪声模型及速度估计的影响。结果表明,基准站坐标序列噪声模型不能由单一的噪声模型表述,其呈现出多样性特征,主要表现为幂律噪声、高斯马尔科夫噪声、闪烁噪声+白噪声特征,且三坐标分量表现出不同的噪声特性;随着时间跨度的增加,坐标时间序列的最优噪声模型、GPS站速度及其不确定度逐渐由发散趋于收敛,随机游走噪声模型的比重有所增加。结果表明10 a以上的时间跨度是较为理想的噪声模型估计尺度。     

不确定性作战任务形式化描述方法

针对复杂作战环境下作战任务的不可预知性特点,对不确定性任务的形式化描述方法进行了深入研究。分析不确定环境导致的任务分解和执行过程中存在的不确定性因素,从任务本身的不确定性、任务之间关系不确定性以及作战单元执行不确定性等方面,对不确定性任务进行了形式化描述,提出了不确定性任务形式化描述流程,最后通过一个实例对所提方法进行了验证。     

Modelling international conflict under conditions of state level economic and political uncertainty

Formal models of international conflict have tended to concentrate on change across the security dimension, assuming that the state level economic and political dimensions are constant. However, the conclusion of the Cold War suggests that over the long run these dimensions are not constant; indeed, the development of economic power, state level limits on defence expenditures, structural impediments to economic change, and several other ‘constants’ clearly do have an endogenous role in international conflict. This paper suggests one strategy for their inclusion as a causal factor in conflict modelling.     

基于一般二元关系的不确定性度量方法研究

针对一般二元关系,从知识的区分能力角度提出一种带有可调节参数的新的不确定性度量-α熵,给出了其在一般二元关系下的重要性质,指出一般二元关系下的α熵是现有多种不确定性度量的扩展,统一了完备和不完备信息系统中知识的不确定性度量.结合知识的α熵,给出了一般二元关系下粗糙集的α精度和α粗糙度的定义,证明了α精度、α粗糙度和知识...     

基于滚动时域的C2组织决策层结构动态适应性优化

针对C2组织决策层结构适应性优化问题,定义了决策层结构与使命的适应性测度,分析了影响C2组织决策层结构的不确定因素,建立了决策层结构适应性优化模型.为了降低决策层结构适应性优化问题求解所面临的不确定性和减少决策层结构变化成本,设计了基于滚动时域的动态适应性优化方法,在提升决策层结构性能的同时控制了决策层结构变化成本.通...