多脉冲导弹可达域优化方法设计与分析

为了更合理地制定导弹的战术指标和作战任务规划,对多脉冲导弹可达域进行研究。通过引入加权的纵程和横程的组合性能指标函数,将可达域的优化问题转化为最优控制问题,建立以飞行攻角和侧滑角为双优化设计变量的多阶段多约束优化模型,采用hp自适应伪谱法对其进行求解,并着重分析多脉冲导弹发动机参数和终端约束条件对导弹可达域的影响。仿真结果表明,hp自适应伪谱法能有效解决多阶段多约束的多脉冲导弹可达域优化问题,且多脉冲导弹脉冲发动机时间间隔越小,推力比越大,装药比越小,导弹的可达域越大,相比于终端速度对可达域的影响,终端弹道倾角对可达区域的影响较小。     

数字化部队作战能力评估指标体系构建

探讨了数字化部队作战能力评估的指导思想和原则,从现代战争系统模型分解图的指标构建思想出发,以系统科学与工程理论为指导,构建数字化部队战争系统模型分解图,将现代战争系统分解成部队与武器子系统、电子信息子系统、指挥决策子系统和综合保障子系统,并分别对各子系统的能力指标内涵进行了详细解释,用信息系统描述了各指标体系的能力构成。     

Network design for time‐constrained delivery

To meet customer demand, delivery companies are offering an increasing number of time‐definite services. In this article, we examine the strategic design of delivery networks which can efficiently provide these services. Because of the high cost of direct connections, we focus on tree‐structured networks. As it may not be possible to identify a tree‐structured network that satisfies all of the delivery guarantees, we allow these guarantees to be violated but seek to minimize the sum of the violations. We establish the complexity of the problem and exploit an empirically identified solution structure to create new neighborhoods which improve solution values over more general neighborhood structures. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Optimal capacity in a coordinated supply chain

We consider a supply chain in which a retailer faces a stochastic demand, incurs backorder and inventory holding costs and uses a periodic review system to place orders from a manufacturer. The manufacturer must fill the entire order. The manufacturer incurs costs of overtime and undertime if the order deviates from the planned production capacity. We determine the optimal capacity for the manufacturer in case there is no coordination with the retailer as well as in case there is full coordination with the retailer. When there is no coordination the optimal capacity for the manufacturer is found by solving a newsvendor problem. When there is coordination, we present a dynamic programming formulation and establish that the optimal ordering policy for the retailer is characterized by two parameters. The optimal coordinated capacity for the manufacturer can then be obtained by solving a nonlinear programming problem. We present an efficient exact algorithm and a heuristic algorithm for computing the manufacturer's capacity. We discuss the impact of coordination on the supply chain cost as well as on the manufacturer's capacity. We also identify the situations in which coordination is most beneficial. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Risk‐sensitive sizing of responsive facilities

We develop a risk‐sensitive strategic facility sizing model that makes use of readily obtainable data and addresses both capacity and responsiveness considerations. We focus on facilities whose original size cannot be adjusted over time and limits the total production equipment they can hold, which is added sequentially during a finite planning horizon. The model is parsimonious by design for compatibility with the nature of available data during early planning stages. We model demand via a univariate random variable with arbitrary forecast profiles for equipment expansion, and assume the supporting equipment additions are continuous and decided ex‐post. Under constant absolute risk aversion, operating profits are the closed‐form solution to a nontrivial linear program, thus characterizing the sizing decision via a single first‐order condition. This solution has several desired features, including the optimal facility size being eventually decreasing in forecast uncertainty and decreasing in risk aversion, as well as being generally robust to demand forecast uncertainty and cost errors. We provide structural results and show that ignoring risk considerations can lead to poor facility sizing decisions that deteriorate with increased forecast uncertainty. Existing models ignore risk considerations and assume the facility size can be adjusted over time, effectively shortening the planning horizon. Our main contribution is in addressing the problem that arises when that assumption is relaxed and, as a result, risk sensitivity and the challenges introduced by longer planning horizons and higher uncertainty must be considered. Finally, we derive accurate spreadsheet‐implementable approximations to the optimal solution, which make this model a practical capacity planning tool.© 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

In this study, we illustrate a real‐time approximate dynamic programming (RTADP) method for solving multistage capacity decision problems in a stochastic manufacturing environment, by using an exemplary three‐stage manufacturing system with recycle. The system is a moderate size queuing network, which experiences stochastic variations in demand and product yield. The dynamic capacity decision problem is formulated as a Markov decision process (MDP). The proposed RTADP method starts with a set of heuristics and learns a superior quality solution by interacting with the stochastic system via simulation. The curse‐of‐dimensionality associated with DP methods is alleviated by the adoption of several notions including “evolving set of relevant states,” for which the value function table is built and updated, “adaptive action set” for keeping track of attractive action candidates, and “nonparametric k nearest neighbor averager” for value function approximation. The performance of the learned solution is evaluated against (1) an “ideal” solution derived using a mixed integer programming (MIP) formulation, which assumes full knowledge of future realized values of the stochastic variables (2) a myopic heuristic solution, and (3) a sample path based rolling horizon MIP solution. The policy learned through the RTADP method turned out to be superior to polices of 2 and 3. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

Revenue management with aircraft reassignment flexibility

A well‐studied problem in airline revenue management is the optimal allocation of seat inventory among different fare‐classes, given a capacity for the flight and a demand distribution for each class. In practice, capacity on a flight does not have to be fixed; airlines can exercise some flexibility on the supply side by swapping aircraft of different capacities between flights as partial booking information is gathered. This provides the airline with the capability to more effectively match their supply and demand. In this paper, we study the seat inventory control problem considering the aircraft swapping option. For theoretical and practical purposes, we restrict our attention to the class of booking limit policies. Our analytical results demonstrate that booking limits considering the swapping option can be considerably different from those under fixed capacity. We also show that principles on the relationship between the optimal booking limits and demand characteristics (size and risk) developed for the fixed‐capacity problem no longer hold when swapping is an option. We develop new principles and insights on how demand characteristics affect the optimal booking limits under the swapping possibility. We also develop an easy to implement heuristic for determining the booking limits under the swapping option and show, through a numerical study, that the heuristic generates revenues close to those under the optimal booking limits. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

基于粗糙集理论的定性推理结果的约束

从分析定性推理结果存在的问题出发,提出定性约束的必要性.总结了几种现有的定性约束,提出一种新的定性约束-粗糙定性约束,利用粗糙集属性约简算法对定性推理结果进行约简.简要介绍了粗糙定性推理软件的总体设计思路流程和功能模块划分.以物资供应保障过程定性推理结果为例,对所得推理结果进行粗糙定性约束,得到重要推理结果,为物资供应保障决策提供参考意见.     

武警部队重大改革必须向“能打胜仗”的战斗力聚焦

从关于国防和军队重大改革的重要论述入手,系统地阐述了武警部队重大改革必须向“能打胜仗”的战斗力聚焦。主要从三个层面进行分析：一是向提高部队整体素质及优化规模结构聚焦;二是向提高部队武器装备保障效能聚焦;三是向增强部队以执勤处突为中心的军事能力聚焦。     

带运力限制及单边时变约束下多出发机场航空战略投送兵力分配模型研究

利用民航力量由多个机场向一个目标机场实施航空战略投送时,由于各民航机场都具有运力限制约束,不可能无限制地快速投送兵力,因此,考虑了在多个出发机场存在运力限制约束的情况下,构建了"投送时间最短,动员机场最少"多目标决策模型,并给出了优化算法和算例.