一类带容量限制的运输问题

考虑一类带容量限制的运输问题.采用构造辅助网络的方法,将运输网络中的每个配送中心均拆分成两个节点,构造出新弧,形成新的网络,把此类运输问题转换为最小费用流问题来解决.并在此基础上,考虑运输网络中配送中心的容量扩张问题.     

基于Petri网的多状态运输网络端端可靠度计算方法

经典的网络可靠性问题认为网络和部件只存在完全工作或完全故障两种状态。但在运输网络中,节点和弧可能处于某种中间状态,即存在多状态特性。描述了一种基于Petri网计算多状态运输网络端端可靠度的方法,节点和弧的能力可以服从任何分布,传输时间是与其当前能力和运输需求有关的的随机值。能力随机有色Petri网被用于模拟系统行为,通过仿真估算多状态运输网络的端端可靠度,同时可以确定可靠度最高的最优路径,最后给出了一些计算实验。     

一种新的运输问题对偶算法

本文给出求解运输问题的一种新的方法——运输问题对偶算法(仍是表上作业法)。最后给出的实例说明本文算法在解决某些问题时比[1]中方法简便。     

军队油料运输网络安全优化研究

军队油料运输路径选择受交通运输网络和运输线路风险的影响和制约。战时,交通运输网络是敌方破坏的重点,油料运输面临很大风险,安全形势非常严峻。合理优化交通运输网络,选择合适的运输路径是避免敌方破坏、保障油料运输安全的重要途径。从不同决策角度出发,选择以总后勤部军事交通运输部为代表的网络规划者和以各级军事代表处及运油分队为代表的运输路径选择者为两级决策者,以实现总体风险均衡和单条运输路径目标最优为出发点,建立双层规划模型,对运输网络进行优化,选择最优运输路径。该法既可降低不同性质的风险,又能兼顾各种风险的相互影响。     

军事物流运输中的最小风险最大流模型构建及求解

文章综合考虑运输风险、弧的容量和网络流量等因素,基于最小费用最大流问题,构建最小风险最大流模型并进行求解,研究军事物流运输中的最小风险路径选择和增广链流量调整问题。实例分析结果表明,最小风险最大流模型,可以较好地应用于军事物流运输路线的选择上。通过获得最优的运输路线,可以为军事物流运输的决策提供理论支持。     

有容量限制的运输问题

具有容量限制的运输问题可以用有界变量的线性规划问题求解,但是问题的规模往往变得很大,给求解带来不便。本文给出求解这一问题的表上作业法。     

弧齿锥齿轮摩擦功率损失计算

基于齿轮啮合原理和摩擦学理论,将弧齿锥齿轮等效为当量直齿圆柱齿轮,并综合考虑啮合点相对滑动速度、法向载荷、摩擦系数等时变性因素和实际重合度的影响,建立弧齿锥齿轮摩擦功率损失计算模型。基于该模型,以某型直升机尾减速器弧齿锥齿轮为对象,对其进行摩擦功率损失计算分析。结果表明,该计算模型考虑因素全面、分析方法简便、计算结果准确可靠,对弧齿锥齿轮摩擦功率损失计算具有参考价值。     

一种面向多制式路径规划的网络模型

随着综合交通运输与导航应用技术的发展,综合利用多种交通方式实施路径规划的应用需求日益迫切,传统的单一制式路径规划系统与服务正在向多制式的方向发展.然而,传统的路径规划模型与算法难以直接应用在多制式的条件下.针对多制式路径规划的特点,构建合理的数据模型是解决该问题的基础.为此,提出了制式切换点的概念,并以此为基础建立了包含多制式图集合、顶点属性表和切换点矩阵三个主要部分的多制式网络模型,并在真实的城市道路网数据集上进行了多制式网络构建实验.该工作能够从理论和实践两个方面为多制式路径规划算法的设计提供基础性的技术支持.     

军事物流配送中心作业流程建模与仿真

军事物流配送中心是军事物流的重要组成部分,加强军事物流配送中心的作业研究对于提高我军后勤保障能力有着重要的现实意义。根据军事物流配送中心的作业特点,分析了军事物流配送中心作业流程,建立了相应的作业过程仿真模型,并用Flex-sim仿真软件对军事物流配送中心作业流程进行了仿真。通过仿真结果分析,找出了作业流程中的瓶颈,为配送中心资源和流程的改进提供了依据。     

基于火力打击的装备物资配送中心选址模型

战时装备物资配送中心的选址优劣与否对作战效果影响很大,有时甚至会影响到战斗的结果.针对战时装备配送中心选址的安全性要求,深入剖析了现代战争条件下装备物资配送中心选址模型的影响要素,建立了基于火力打击的费用最少和时间最短的装备物资配送中心选址模型,以及同时考虑时间和费用的装备物资配送中心的综合权衡模型,并给出了时间、费用最小模型的求解流程.     

基于动态模型的机场配电网潮流计算新方法

机场配电网因非常情况成为孤立电力系统后，配电系统的电压、潮流和频率等发生巨大变化，传统的潮流计算方法往往会出现收敛性差、计算结果与实际不相符的情况。提出的机场配电网动态潮流计算模型能有效解决此类问题，阐述了机场配电网动态潮流计算模型的构成原理、算法并给出相应算例。通过算例计算证明了动态潮流计算模型适用于计算机场配电网的潮流。     

Machine scheduling with an availability constraint and job delivery coordination

In this paper we study the scheduling problem that considers both production and job delivery at the same time with machine availability considerations. Only one vehicle is available to deliver jobs in a fixed transportation time to a distribution center. The vehicle can load at most K jobs as a delivery batch in one shipment due to the vehicle capacity constraint. The objective is to minimize the arrival time of the last delivery batch to the distribution center. Since machines may not always be available over the production period in real life due to preventive maintenance, we incorporate machine availability into the models. Three scenarios of the problem are studied. For the problem in which the jobs are processed on a single machine and the jobs interrupted by the unavailable machine interval are resumable, we provide a polynomial algorithm to solve the problem optimally. For the problem in which the jobs are processed on a single machine and the interrupted jobs are nonresumable, we first show that the problem is NP‐hard. We then propose a heuristic with a worst‐case error bound of 1/2 and show that the bound is tight. For the problem in which the jobs are processed on either one of two parallel machines, where only one machine has an unavailable interval and the interrupted jobs are resumable, we propose a heuristic with a worst‐case error bound of 2/3. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

电磁发射系统以太网拓扑结构建模优化

拓扑结构优化模型是网络中的一类重要模型，可以有效地优化系统整体链路性能。针对电磁发射系统以太网拓扑结构中部分节点和链路的负载过大，一旦发生堵塞，将会影响网络中关键链路性能的问题，建立网络拓扑结构优化的多目标规划模型，并提出一套基于基因环操作的遗传算法对其进行求解，通过仿真得出最优的网络拓扑结构。根据仿真结果修改实际网络节点默认配置参数，结果显示该模型和算法能有效均衡负载，降低网络冲突率，且不需要改变电磁发射系统以太网的物理链路，不会增加额外成本，对电磁发射类系统具有普适性的意义。     

基于神经网络的舰船建造费用预测分析

采用了一种基于神经网络的舰船建造费预测方法 .计算结果表明 ,这种方法与传统的参数法相比较 ,有更好的估算精度 ,因而该方法可以作为研究此类问题的新途径     

基于代理群的军事自组网拓扑搜索算法

分析现有网络管理模式的基础上,针对军事移动自组网的特点,提出了一种基于动态代理群的网络管理模式,并实现了动态代理群网络管理模式的网络拓扑结构搜索算法,最后对该拓扑搜索算法的有效性、正确性及复杂度进行分析论证.实验证明该算法可以很好地解决节点频繁移动带来的需要实时反映网络拓扑结构的问题.     

Integrated scheduling of loading and transportation with tractors and semitrailers separated

Motivated by some practical applications, we study a new integrated loading and transportation scheduling problem. Given a set of jobs, a single crane is available to load jobs, one by one, onto semitrailers with a given capacity. Loaded semitrailers are assigned to tractors for transportation tasks. Subject to limited resources (crane, semitrailers, and tractors), the problem is to determine (1) an assignment of jobs to semitrailers for loading tasks, (2) a sequence for the crane to load jobs onto semitrailers, (3) an assignment of loaded semitrailers to tractors for transportation tasks, and (4) a transportation schedule of assigned tractors such that the completion time of the last transportation task is minimized. We first formulate the problem as a mixed integer linear programming model (MILPM) and prove that the problem is strongly NP‐hard. Then, optimality properties are provided which are useful in establishing an improved MILPM and designing solution algorithms. We develop a constructive heuristic, two LP‐based heuristics, and a recovering beam search heuristic to solve this problem. An improved procedure for solutions by heuristics is also presented. Furthermore, two branch‐and‐bound (B&B) algorithms with two different lower bounds are developed to solve the problem to optimality. Finally, computational experiments using both real data and randomly generated data demonstrate that our heuristics are highly efficient and effective. In terms of computational time and the number of instances solved to optimality in a time limit, the B&B algorithms are better than solving the MILPM. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 416–433, 2015     

Solving generalized transportation problems via pure transportation problems

This paper investigates certain issues of coefficient sensitivity in generalized network problems when such problems have small gains or losses. In these instances, it might be computationally advantageous to temporarily ignore these gains or losses and solve the resultant “pure” network problem. Subsequently, the optimal solution to the pure problem could be used to derive the optimal solution to the original generalized network problem. In this paper we focus on generalized transportation problems and consider the following question: Given an optimal solution to the pure transportation problem, under what conditions will the optimal solution to the original generalized transportation problem have the same basic variables? We study special cases of the generalized transportation problem in terms of convexity with respect to a basis. For the special case when all gains or losses are identical, we show that convexity holds. We use this result to determine conditions on the magnitude of the gains or losses such that the optimal solutions to both the generalized transportation problem and the associated pure transportation problem have the same basic variables. For more general cases, we establish sufficient conditions for convexity and feasibility. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 666–685, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10034     

战时交通运输路径优化研究

以战时交通运输路径优化问题为研究对象,分析问题特点,考虑多式联运,以运输时间代价、运输费用代价、路段和运输节点的危险性代价为优化目标,建立起广义运输代价最小的运输路径优化模型,并设计了蚁群算法来求解问题模型。给出的算例表明,文中模型符合战时交通运输的特点和实际需要,可为确定战时运输路径提供决策支持,而采用的蚁群算法是求解该问题的一种有效方法。