基于粒子群实验寻优算法的后勤装备维修器材仓库布局选址

针对我军后勤装备维修器材仓库分布点多面广、配送时效性不高、整体保障效益偏低等问题,建立了基于混合整数规划的仓库布局选址模型,设计了粒子群实验寻优算法进行求解。以SY战区为例,验证了模型和算法的有效性,得到了该战区的后勤装备;维修器材仓库布局方案,并与基本粒子群算法进行了对比分析。     

考虑不确定性的多阶段装备维修器材供应优化方法

装备维修器材供应是作战部队持续保持战斗力的关键。考虑多阶段作战行动中,战场形势、部队位置及需求量等不确定性,将野战仓库选址、需求分配、供应路径规划融合为一类选址-路径组合优化问题,构建基于情境的多阶段混合整数规划模型。设计一种两阶段迭代启发式算法对问题进行求解。基于20个算例的数值实验,证明了所提出的模型及算法在具有高度不确定性的多阶段装备维修器材供应保障中的有效性。     

基于改进FPA和SVM的装备器材需求预测

精确预测已成为制约器材筹措决策的重难点问题.对此,在对国内外研究分析基础上,提出适用于复杂装备保障的消耗性器材需求预测方法.针对器材消耗规律,构建基于支持向量机的器材需求预测模型,并提出模型约束优化指标;针对器材需求预测约束优化的不确定性,将佳点集种群初始化、Deb可行性比较法、着约束法融入花朵授粉算法,设计面向SVM模型优化的花朵授粉求解算法;以某建制单位器材供应为例,验证方法的可行性和优越性.     

装备维修器材生产路径决策的两阶启发式算法

当前装备供应保障系统中维修器材存在短缺、积压以及配送系统效率低下等问题,亟须对生产、库存和配送作业环节进行集成优化。为客观反映各个决策环节,将该问题公式化为一个混合整数线性规划模型,针对该模型多变量、多约束的特点,提出了一个基于数学规划的两阶启发式算法对其进行求解。结合算例,检验模型的可行性,并选取求解器CPLEX和一个类似的迭代算法与该算法在求解质量和运算时间方面进行对比与分析。结果表明,提出的模型是合理可行的,该算法在求解不同规模实例时表现出优异的性能。     

基于任务的装备器材多阶段动态供应策略与模型

针对传统的任务装备器材保障模式时效性、灵活性、持续性较差的问题,提出一种基于任务的装备器材多阶段动态供应策略,以总保障成本最小、超储器材利用率最高、任务重要度最高为目标,建立了基于任务的装备器材多阶段动态供应调度模型,并采用动态粒子群算法对模型进行了求解,最后通过实例仿真验证了模型和策略的合理性、可行性。     

配套装备器材的库存与运输集成优化研究

针对我军配套装备器材订货的特点，在考虑库存容量空间限制与整套装备的最低期望满足率两种约束条件下，建立了配套装备器材的库存与运输优化模型，并应用改进的动态规划方法进行求解。结果表明：应用库存与运输的优化模型，在保障军事目标实现的前提下，有效地降低了物流成本。     

装备器材保障资源调度决策模型及算法

装备器材保障资源调度问题是一个非常复杂的问题,根据其优化目标要求,从保障时间最短、保障耗费最低、安全性最高3个方面建立了该问题的多目标优化模型,并通过目标优先度决策将其转化为单目标模型;接着,采用两阶段法进行求解,将其分为最优路径决策、器材分配决策两个阶段进行决策优化,在明确资源点到需求点之间的最优路径后再进行器材资源的分配;并分别采用基于小生境的自适应遗传算法和基于生成树的遗传算法进行求解。通过实例分析,求解结果能够满足装备器材保障的要求,表明所构建的决策模型和算法是有效的。     

基于任务的两阶段装备器材供应调度模型

针对"尽可能多"的传统装备器材(简称"器材")供应保障模式存在的资源浪费问题,将任务器材供应分为任务准备和任务执行2个阶段,在军民融合背景下提出了一种系统化的两阶段器材供应调度策略,建立了两阶段器材供应调度优化模型,并进行了示例仿真分析。研究结果表明:与传统供应策略相比,即使器材供应前期需求预测准确率较低,该调度模型仍具有明显优势,可为基于任务的装备保障提供决策参考。     

BP神经网络的遗传模拟退火算法动态选址仿真

针对战区装备保障点动态选址问题的广义最大覆盖选址模型,综合分析传统的启发式算法全局、局部搜索中的优缺点,提出一种基于BP神经网络的遗传模拟退火算法,并将其运用于战区装备保障点动态选址决策实际问题中,对该算法进行了仿真研究,给出具体实例的仿真结果验证了该算法求解最优解的高效性以及运算的高收敛速度.     

网电对抗战备器材储备布局物流场模型研究

网电对抗战备器材储备布局的科学性、合理性,直接影响制约战时网电对抗维修器材供应,影响网电对抗装备保障的效能。着眼网电对抗战备器材储备布局的目标,立足网电对抗战备器材储备布局的原则,基于物流场理论构建网电对抗战备器材储备布局模型,并运用线性规划和Matlab进行模型求解,获得网电对抗战备器材储备布局的优化方案。     

基于筹措供应中心的装备器材保障研究

将先进的物流理论和供应链管理思想应用于装备器材保障中,阐述了建立装备器材筹措供应中心的重要性,构建了基于筹措供应中心的装备器材保障体系,设计了基于筹措供应中心的器材保障物流网络和器材保障信息管理,探讨了该模式下装备器材保障体系的运作机制,从而实现了装备器材保障管理的系统性和集成性,提高了装备器材保障的时效性和敏捷性。     

远海作战装备供应链体系架构

信息化使战争的节奏加快,如何满足快节奏战争对装备的需求,无疑是军事保障领域值得研究的一个问题.供应链思想被引入军事物资保障系统后,已在多个领域发挥了显著的效用.建立装备供应链网络对提升远海作战装备供应能力既有现实意义又是可行的,这是因为：一方面信息化条件下远海作战需要更有效率的装备供应体系,另一方面企业供应链为装备供应链提供了可以借鉴的模式.本文通过对远海作战装备供应链目标和特征的分析,参照企业供应链和美军海上供应链建设的情况,建立了远海作战装备供应链网络,并对供应链流程进行了说明.     

Models for production planning under power interruptions

We present a robust optimization model for production planning under the assumption that electricity supply is subject to uncertain interruptions caused by participation in interruptible load contracts (ILCs). The objective is to minimize the cost of electricity used for production while providing a robust production plan which ensures demand satisfaction under all possible interruption scenarios. The combinatorial size of the set of interruption scenarios makes this a challenging problem. Furthermore, we assume that no probabilistic information is known about the supply uncertainty: we only use the information given in the ILC to identify an uncertainty set that captures the possible scenarios. We construct a general robust framework to handle this uncertainty and present a heuristic to compute a good feasible solution of the robust model. We provide computational experiments on a real‐world example and compare the performance of an exact solver applied to the robust model with that of the heuristic procedure. Finally, we include the operational impact of interruptions such as “recovery modes” in the definition of the uncertainty set. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

基于证据理论的战时军械维修器材供应链性能评价

在一般供应链性能评价指标体系的基础上,结合现代战争中军械维修器材供应链的特点,从资源、输出和柔性三个角度构建了战时军械维修器材供应链性能评价的指标体系.考虑到战争环境下信息的模糊性和不确定性,建立了战时军械维修器材供应链性能评价的证据理论模型.以某战时军械维修器材供应链为例,基于构建的战时军械维修器材供应链性能评价指标体系和模型进行案例研究.结果表明,基于证据理论构建的战时军械维修器材供应链性能评价模型是可行的,有效的.     

近空间飞行器固体火箭助推器/助推弹道总体设计优化

研究一种近空间飞行器的固体火箭助推器/助推弹道总体优化问题.在选定喷管构型、推进剂、壳体材料、绝热层材料及药柱结构的前提下,建立包含热力学分析与计算、质量分析与计算、气动力分析与计算和弹道设计与计算的系统分析模型,采用一种基于可行性规则与结合模拟退火的混合粒子群优化算法求解最优解.优化结果表明建立的系统分析模型和采用的...     

基于多资源点的装备应急器材调度决策模型

针对装备应急器材调度决策问题,从调度路径优化和调度计划分配2个方面,研究了其多目标优化模型的构建。将资源点划分为若干级别来确定资源点选取的优先次序,通过先求解资源点与需求点之间的最优路径,后求解器材资源分配量的思路,建立了装备应急器材调度决策的广义最优路径模型和运输模型,采用改进的Dijkstra算法对模型进行求解,仿真结果表明:所构建的决策模型及算法是有效的。     

Generation and storage dispatch in electricity networks with generator disruptions

We present methods for optimizing generation and storage decisions in an electricity network with multiple unreliable generators, each colocated with one energy storage unit (e.g., battery), and multiple loads under power flow constraints. Our model chooses the amount of energy produced by each generator and the amount of energy stored in each battery in every time period in order to minimize power generation and storage costs when each generator faces stochastic Markovian supply disruptions. This problem cannot be optimized easily using stochastic programming and/or dynamic programming approaches. Therefore, in this study, we present several heuristic methods to find an approximate optimal solution for this system. Each heuristic involves decomposing the network into several single‐generator, single‐battery, multiload systems and solving them optimally using dynamic programming, then obtaining a solution for the original problem by recombining. We discuss the computational performance of the proposed heuristics as well as insights gained from the models. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 493–511, 2015     

Single‐commodity stochastic network design under demand and topological uncertainties with insufficient data

Stochastic network design is fundamental to transportation and logistic problems in practice, yet faces new modeling and computational challenges resulted from heterogeneous sources of uncertainties and their unknown distributions given limited data. In this article, we design arcs in a network to optimize the cost of single‐commodity flows under random demand and arc disruptions. We minimize the network design cost plus cost associated with network performance under uncertainty evaluated by two schemes. The first scheme restricts demand and arc capacities in budgeted uncertainty sets and minimizes the worst‐case cost of supply generation and network flows for any possible realizations. The second scheme generates a finite set of samples from statistical information (e.g., moments) of data and minimizes the expected cost of supplies and flows, for which we bound the worst‐case cost using budgeted uncertainty sets. We develop cutting‐plane algorithms for solving the mixed‐integer nonlinear programming reformulations of the problem under the two schemes. We compare the computational efficacy of different approaches and analyze the results by testing diverse instances of random and real‐world networks. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 154–173, 2017     

Optimal power control in a wireless network using a model with stochastic link coefficients

This paper addresses optimal power allocation in a wireless communication network under uncertainty. The paper introduces a framework for optimal transmit power allocation in a wireless network where both the useful and interference coefficients are random. The new approach to power control is based on a stochastic programming formulation with probabilistic SIR constraints. This allows to state the power allocation problem as a convex optimization problem assuming normally or log‐normally distributed communication link coefficients. Numerical examples illustrate the performance of the optimal stochastic power allocation. A distributed algorithm for the decentralized solution of the stochastic power allocation problem is discussed. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005