基于战时弹药消耗及补给数据的弹药储备量控制方法

针对战时基于定点调拨的弹药储备与基于定期调拨的弹药储备中存在的断供与盲供问题,从弹药消耗及补给数据出发,围绕弹药消耗量、补给量与储备量之间的相互关系,以优化技术为手段,兼顾基于定点调拨弹药储备与基于定期调拨弹药储备的优点,通过寻求最佳弹药储备量和最佳弹药补给点的方法,实现了弹药储备量的优化控制,为今后的弹药储备控制方法研究提供了理论依据和参考。     

航空弹药供应保障存在的问题及对策

在现代高技术信息化战争中,航空弹药地位和作用日渐突出。在分析了信息化条件下现代战争对航空弹药供应保障提出的新需求基础上,指出了航空弹药供应保障存在的不足,并从航空弹药的储备、管理和供应三个方面分别提出了相应的对策。研究表明,着眼应急作战的实际需要,搞好航空弹药供应保障,提高应急作战弹药供应保障能力,是摆在面前的一个现实而又紧迫的任务。     

弹药实物储备规模控制模型构建

针对国内外弹药储备规模控制理论及模型研究的现状,讨论了当前弹药实物储备相关模型的种类及存在的问题;运用库存控制物流理论,从需求牵引、风险控制、动态调节3个方面研究了模型构建的思路与原则,分析了弹药储备系统的基本构成和相互关系,基于需求和多因素影响建立了弹药实物储备规模控制模型,并进行了演示运用。     

基于蚁群算法的航空弹药需求测算

智能化是现代航空弹药需求与指挥控制系统的发展趋势,如何进行合理快速地调拨航空弹药是系统设计过程中的关键任务之一。为此,提出了依据目标对航空弹药进行选择的策略,利用蚁群算法对战斗目标进行聚类分析,对各类目标进行模糊综合评判,从而确定装备出动方案,依据弹药与装备的关系,对满足既定保障度的弹药需求量建立模型,并计算出满足既定保障度的弹药供应量,为战前对战场态势预估,实现弹药战时及时准确调拨,为作战弹药准备提供依据。     

弹药保障CGF智能决策模型研究与实现

弹药保障CGF智能决策系统是装备保障效能评估系统必不可少的组成部分,其核心是对人类决策行为的建模与仿真.在介绍智能决策含义和决策过程的基础上,重点研究和分析了CGF智能决策行为,构建了CGF智能决策模型.针对决策过程中由于无法获得人脑思维方式而导致行为模型的表达、描述、推理等受到怀疑的问题,在弹药保障CGF智能决策模型中,将决策行为分解为任务决策、过程决策和动作决策3个步骤,接近于人类思维方式.同时,对实现弹药保障CGF智能决策具有关键作用的任务决策原则、过程决策方法和动作决策规则进行了研究,并给出了应用实例.实例证明,弹药保障CGF智能决策方法逻辑清晰,易于理解和维护,便于实现.     

弹药库房储存物资燃爆事故敏感度评估

为提高后方仓库安全管理工作水平,有效防范意外燃爆事故发生,依据弹药"共同储存原则",确定了14类弹药库房储存物资燃爆事故敏感度参数及评估标准,构建了燃爆事故敏感度评估模型,并选取某弹药洞库进行了实例评估。评估结果表明:该弹药洞库燃爆事故敏感度为"较敏感",与洞库实际情况相符,构建的评估模型有效可行。评估结果对提高弹药库房安全管理定量化水平具有借鉴参考价值。     

基于失供概率的弹药储备构成分析

弹药储备与失供问题是战时弹药供应决策的核心问题之一。以师规模的野战阵地防御战为例,运用弹药消耗模式仿真模型进行弹药储备量与失供概率关系定量分析,为合理确定弹药储备构成提供科学的辅助决策手段。     

弹药供应保障指挥系统工作流建模研究

从面向对象的角度分析了弹药供应保障指挥业务流程,建立了面向对象的弹药供应保障指挥系统工作流概念模型,并以此为依据采用CPN过程建模技术进一步建立了弹药供应保障指挥系统工作流的OOCPN解析模型,为弹药补给时机和数量的控制决策提供了定量化的模型依据。由于建模方法采用了面向对象技术,因此能有效降低系统建模的复杂度,提高建模的效率,能更好地满足系统开放性、层次性和动态重组的需要,具有很高的实用价值。     

信息系统体系作战弹药保障能力评估

弹药信息化是武器装备信息化的重要组成部分,直接影响战斗力的生成。如何分析、评估保障单位在信息系统体系作战弹药信息化保障能力的建设水平,对我军信息化建设至关重要。在分析影响弹药信息化保障能力形成的主要因素的基础上,构建了符合我军弹药信息化保障能力特点的评估指标体系,提出了一种基于主成分和集对分析法综合分析的基于信息系统体系作战弹药信息化保障能力评估方法,通过该方法可求得指标权重,最终获得被评估单位弹药信息化保障能力的整体建设水平。结合实例分析,验证构建的评估模型能够用于我军基于信息系统体系作战弹药信息化保障能力的评估,进一步为如何提高弹药信息化保障能力提供技术指导。     

基于ISM的战略级弹药订购因素分析

订购因素分析是实施战略级弹药订购亟需解决的关键性问题,为详细而准确地筹划、建设和运用弹药资源,实现合理的弹药储备规模、储备结构以进行精准弹药保障具备重大意义。在弹药订购目标分析的基础上,从顶层设计、需求来源、弹药后勤能力、生产能力储备、订购经济效益、弹药保障效能等6个方面出发,构建由16个因素组成的弹药订购决策影响因素体系,利用解释结构模型对影响因素进行分析,得到了战略任务、经费投入、储存能力、生产能力4个弹药订购关键影响因素,为战略级弹药订购工作改进提供基础。     

带优先级的单类型航空弹药转运多目标规划模型

针对航母航空弹药转运过程非常复杂、涉及设备多、要求高的特点,在对其流程进行细致分析的基础上,将其抽象为一个两阶段多目标规划问题。同时,深入分析了转运过程中的各种约束条件、构建了该问题的两阶段优化模型。建模时,不仅考虑了武器升降机的有效利用、弹药量的合理分配等因素,还考虑了转运时对于不同类型弹药转运优先级与停机区弹药需求优先级的要求。通过模型优化,在满足转运优先级要求的基础上,能有效提高航空弹药的转运效率。     

战时弹药供应协同调运模型研究

弹药协同调运是战时弹药保障工作中的重要环节,其协同调运的合理性将直接影响到弹药保障工作的顺利进行.针对弹药的调运问题,从战时技术实施与应用角度研究弹药的调运问题,以到达需求点的运输时间、弹药输送车数量以及弹药损失量为优化目标,建立一种多目标决策模型,为缩短运输时间、减少弹药输送车数量、提高安全到达需求点的弹药量提供一种实用的方法.     

陆军师进攻战斗弹药保障辅助决策模型

本文依据师弹药保障的特点,通过对历次作战军械保障资料的统计研究,建立了动态自适应弹药消耗预计模型和弹药保障方案目标规划模型,并给出了计算机程序实现框图。     

Bayes adaptive control of two-echelon inventory systems,II: The multistation case

The present paper extends the results of [7] to cases of multistation lower echelon. For this purpose an algorithm for the optimal allocation of the upper echelon stock among the lower echelon stations is developed. The policy of ordering for the upper echelon is an extension of the Bayes prediction policy developed in [7]. Explicit formulae are presented for the execution of this policy. Several simulation runs are presented and analyzed for the purpose of obtaining information on the behavior of the system, under the above control policy, over short and long periods.     

A two-echelon inventory model with purchases,dispositions, shipments,returns and transshipments

This paper presents a one-period two-echelon inventory model with one warehouse in the first echelon and n warehouses in the second echelon. At the beginning of the period the stock levels at all facilities are adjusted by purchasing or disposing of items at the first echelon, returning or shipping items between the echelons and transshipping items within the second echelon. During the period, demands (which may be negative) are placed on all warehouses in the second echelon and an attempt is made to satisfy shortages either by an expedited shipment from the first echelon to the second echelon or an expedited transshipment within the second echelon. The decision problem is to choose an initial stock level at the first echelon (by a purchase or a disposition) and an initial allocation so as to minimize the initial stock movement costs during the period plus inventory carrying costs and system shortage costs at the end of the period. It is shown that the objective function takes on one of four forms, depending on the relative magnitudes of the various shipping costs. All four forms of the objective function are derived and proven to be convex. Several applications of this general model are considered. We also consider multi-period extensions of the general model and an important special case is solved explicitly.     

A two‐echelon inventory‐location problem with service considerations

We study the problem of designing a two‐echelon spare parts inventory system consisting of a central plant and a number of service centers each serving a set of customers with stochastic demand. Processing and storage capacities at both levels of facilities are limited. The manufacturing process is modeled as a queuing system at the plant. The goal is to optimize the base‐stock levels at both echelons, the location of service centers, and the allocation of customers to centers simultaneously, subject to service constraints. A mixed integer nonlinear programming model (MINLP) is formulated to minimize the total expected cost of the system. The problem is NP‐hard and a Lagrangian heuristic is proposed. We present computational results and discuss the trade‐off between cost and service. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

合成坦克分队最佳火力分配模型

实际战斗中敌我双方均以多兵种进行交战,在兰切斯特方程基础上,利用不同作战单位的相对作战指数,以及各种作战单位之间的交战强度、掩护强度和循环交战强度,建立合成坦克分队最佳火力分配算法,并应用该算法定量计算二对二作战中坦克分队火力最佳分配的方案,为定量研究合成坦克分队火力运用打下了基础。     

基于0-1规划的弹种决策与发射时序优化

对于身管发射武器系统,同一发射单元使用不同弹种完成作战任务时,需要确立合适的弹种决策与最佳的发射时机.提出用O-1变量来描述弹种决策变量.通过时弹种发射机制及武器系统控制特点进行分析,构造多种0-1变量用以描述武器系统作战时序之间的约束关系,建立了弹种发射时序的0-1规划模型,并用LINGO软件实现了0-1规划的求解.给出了典型应用实例,进行了仿真计算,结果表明,该方法简单可行.     

An optimum multiechelon repair policy and stockage model

Currently, sophisticated multiechelon models compute stockage quantities for spares and repair parts that will minimize total inventory investment while achieving a target level of weapon system operational availability. The maintenance policies to be followed are input to the stockage models. The Optimum Allocation of Test Equipment/Manpower Evaluated Against Logistics (OATMEAL) model will determine optimum maintenance as well as stockage policies for a weapon system. Specifically, it will determine at which echelon each maintenance function should be performed, including an option for component or module throwaway. Test equipment requirements to handle work load at each echelon are simultaneously optimized. Mixed-integer programming (MIP) combined with a Lagrangian approach are used to do the constrained cost minimization, that is, to minimize all costs dependent on maintenance and stockage policies while achieving a target weapons system operational availability. Real-life test cases are included.     

Bayes adaptive control of two-echelon inventory systems i: development for a special case of one-station lower echelon and monte carlo evaluation

Bayes adaptive control policies are developed in the present paper for the special case of a one-station lower echelon: a Poisson distribution of demand, whose mean is assumed to have a prior gamma distribution. The cost structure is of a common type. The ordering policy for the upper echelon, which minimizes expected cost, is replaced by a new type of policy, called Bayes prediction policy. This policy does not require tedious computations, of the sort required by dynamic programming solutions. The characteristics of the policies are studied by Monte Carlo simulation, and supplemented by further theoretical development.