面向任务的随舰备件配置方法

研究了多阶段任务成功概率的计算方法,根据舰船多阶段任务的特点,建立了随舰备件配置模型.提出了系统修整过程中确定备件配置方案的分析方法与系统执行任务过程中基于粒子群算法的备件配置模型.经实例分析表明:该模型既满足了任务成功概率的要求,又充分利用了舰船排水量和宝贵的备件存储空间,对于随舰备件的配置具有普遍的适用性.     

重力场中低可观测弹道导弹的被动测距

本文介绍跟踪重力场中低观测目标运动的一种估计算法。例如,利用纯角量测跟踪接近的弹道导弹。这种量测可以从一个单一的固定传感器获得,但它仅在短时间内可用。而且,低目标发现概率和高虚警密度造成一种困难的低观测环境。一种算法采用概率数据互联并结合最大似然估计法,可以控制误警和小于一的目标的发现概率。本文还介绍杂波中的克拉默—拉奥下界,它确定了在虚警存在和发现概率小于一的情况下,估计器在解这个问题时可以达到最好的精度。本文建议的估计器被证明是有效的,即它满足克拉默-拉奥下界,即使对于低可观测的有6dB平均信噪比的波动目标也是有效的。对于单扫描发现概率为0.6的自由飞行的弹道导弹,其跟踪探测概率可以达到0.99而假航迹认可概率却很小。     

舰载雷达发现目标的效能概率计算

根据舰载雷达保障火炮射击任务的要求,结合火炮自身使用特点,提出舰载雷达发现目标的效能概率计算问题。应用概率分析方法,对多种距离上舰载雷达发现目标保障火炮系统有效射击的概率进行了推导,得出舰载雷达保障火炮系统有效射击的概率计算公式,并进行了实例分析。实际作战运用中,可以应用此算法对火炮系统的射击概率计算,可以较好地保障火炮系统的射击准备时间,但影响实际火炮射击的因素很多,表征雷达发现目标的效能指标也很多,应综合考虑。     

AWGN信道下线性分组码的差错概率下界分析

提出了一种线性分组码的最大似然译码(ML-decoding)差错概率下界的计算方法。差错概率的下界优化实质上是对联合事件概率下界的优化,算法结合改进的Dawson-Sankoff界的优化准则,提出了AWGN信道下线性分组码差错冗余事件的判决准则,得到了误码率下界的计算表达式。该表达式只依赖码字的Hamming重量分布与信噪比,较之类deCaens界与类KAT界,本算法得到的下界更紧,计算量更低。针对LDPC等线性分组码的数值结果证明了算法的优越性能。     

多核系统中基于动态松弛时间回收的节能实时调度算法

许多嵌入式实时任务的实际执行时间往往小于最坏情况执行时间,因此可以产生大量的动态松弛时间.针对时限等于周期的偶发任务集,提出一种基于动态松弛时间回收的多核系统节能实时调度算法LRE-DVFS-ALL.该算法基于最优在线调度算法LRE-TL,利用TL面内节能实时调度思想,在每个TL面的提前完成时刻实现动态松弛时间回收,降...     

BSC信道下线性分组码的差错概率下界分析

针对BSC信道,提出了一种线性分组码的最大似然译码差错概率下界的计算方法.根据最大似然译码算法原理,首先将译码差错概率转化为差错事件的联合概率,基于改进的Dawson-Sankoff界的优化准则,推导出BSC信道下线性分组码差错冗余事件的判决准则,最后得到差错概率下界的计算表达式.该下界只依赖于码字的Hamming重量...     

地空导弹维修保障能力评估与备件优化模型

地空导弹武器系统维修保障能力评估与备件优化是制定维修保障方案的重要内容,能够对平时和战时防空作战任务的维修保障产生重大影响.运用更新过程理论,给出了部件寿命服从指数分布和威布尔分布情况下,单部件和多个同种部件的备件满足率模型.在备件满足率模型的基础上,结合地空导弹装备和部件任务结构关系,得到了系统任务成功概率评估模型.在满足任务成功概率与备件费用约束条件下,建立了系统备件携行量优化模型,用边际分析法进行了求解.通过实例验证,得到了满意的结果.该模型已经应用于某地空导弹使用阶段综合保障信息系统.     

投掷式通信干扰机的战斗任务级效能评估模型

针对投掷式通信干扰机战斗任务级效能评估不足的问题,在分析其典型作战任务的基础上,提出了战斗任务级效能指标——压制概率,依据对空域、频域、时域的覆盖要求,建立了压制概率的评估数学模型,进行了典型作战任务下压制概率的实例分析,分析结果表明:该指标及模型能比较准确地反应通信发射机与任务区域的相对位置、干扰机排布样式、干扰机数量等因素对投掷式通信干扰机战斗任务级效能的影响.     

弹药装填机器人作业平台仿真系统设计与实现

针对弹药装填机器人作业过程复杂的问题,基于作业任务实用性和可操作性的要求,设计了一种作业平台仿真系统。在深入分析弹药装填机器人作业任务和工作过程的基础上,构建了总体设计方案,研究了仿真系统的稳定性技术,进行了运动控制、数据采集以及传感器精度等硬件部分设计和模块化技术的软件设计,建立了弹药装填机器人仿真系统。仿真结果表明：该设计能够实现对弹药装填机器人的控制和实时作业。     

基于组合函数的弹药装填机器人轨迹规划

针对非确定环境下弹药装填机器人作业过程需满足平稳、连续及实时控制易于实现的要求,提出了基于三次多项式与五次多项式相结合的组合函数的弹药装填机器人轨迹规划方法,并对弹药装填机器人取弹作业进行了轨迹规划和仿真计算,实时得到各关节角度、角速度和角加速度,结果表明:该方法既能保证弹药装填作业过程的平稳性与连续性,又能满足作业轨迹高阶导数连续性的要求.     

Single‐machine scheduling with deadlines to minimize the total weighted late work

We consider scheduling a set of jobs with deadlines to minimize the total weighted late work on a single machine, where the late work of a job is the amount of processing of the job that is scheduled after its due date and before its deadline. This is the first study on scheduling with the late work criterion under the deadline restriction. In this paper, we show that (i) the problem is unary NP‐hard even if all the jobs have a unit weight, (ii) the problem is binary NP‐hard and admits a pseudo‐polynomial‐time algorithm and a fully polynomial‐time approximation scheme if all the jobs have a common due date, and (iii) some special cases of the problem are polynomially solvable.     

带时间窗的相控阵雷达实时任务调度方法

为了解决传统相控阵雷达任务调度中采用基于工作方式优先级的方法而存在忽略任务时间紧迫性和重要性的问题,提出了一种基于任务自身工作方式优先级、截止期和空闲时间3个特征参数的相控阵雷达任务调度方法,通过调整参数的权重来适应调度器不同的负载情况,并采用时间窗处理发生冲突的任务请求,确保更多的高优先级任务在调度间隔内被调度。仿真结果表明,所提出的方法能够有效提高任务的调度成功率,明显改善调度器性能。     

Technical note: Worst‐case performance of power‐of‐two policies for serial inventory systems with incremental quantity discounts

This study presents power‐of‐two policies for a serial inventory system with constant demand rate and incremental quantity discounts at the most upstream stage. It is shown that an optimal solution is nested and follows a zero‐inventory ordering policy. To prove the effectiveness of power‐of‐two policies, a lower bound on the optimal cost is obtained. A policy that has a cost within 6% of the lower bound is developed for a fixed base planning period. For a variable base planning period, a 98% effective policy is provided. An extension is included for a system with price dependent holding costs. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Production and transport logistics scheduling with two transport mode choices

This paper considers a new class of scheduling problems arising in logistics systems in which two different transportation modes are available at the stage of product delivery. The mode with the shorter transportation time charges a higher cost. Each job ordered by the customer is first processed in the manufacturing facility and then transported to the customer. There is a due date for each job to arrive to the customer. Our approach integrates the machine scheduling problem in the manufacturing stage with the transportation mode selection problem in the delivery stage to achieve the global maximum benefit. In addition to studying the NP‐hard special case in which no tardy job is allowed, we consider in detail the problem when minimizing the sum of the total transportation cost and the total weighted tardiness cost is the objective. We provide a branch and bound algorithm with two different lower bounds. The effectiveness of the two lower bounds is discussed and compared. We also provide a mathematical model that is solvable by CPLEX. Computational results show that our branch and bound algorithm is more efficient than CPLEX. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

A dynamic allocation heuristic for centralized safety stock

An inventory system that consists of a depot (central warehouse) and retailers (regional warehouses) is considered. The system is replenished regularly on a fixed cycle by an outside supplier. Most of the stock is direct shipped to the retailer locations but some stock is sent to the central warehouse. At the beginning of any one of the periods during the cycle, the central stock can then be completely allocated out to the retailers. In this paper we propose a heuristic method to dynamically (as retailer inventory levels change with time) determine the appropriate period in which to do the allocation. As the optimal method is not tractable, the heuristic's performance is compared against two other approaches. One presets the allocation period, while the other provides a lower bound on the expected shortages of the optimal solution, obtained by assuming that we know ahead of time all of the demands, period by period, in the cycle. The results from extensive simulation experiments show that the dynamic heuristic significantly outperforms the “preset” approach and its performance is reasonably close to the lower bound. Moreover, the logic of the heuristic is appealing and the calculations, associated with using it, are easy to carry out. Sensitivities to various system parameters (such as the safety factor, coefficient of variation of demand, number of regional warehouses, external lead time, and the cycle length) are presented. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

VRML在电传动装甲车辆虚拟试验中的应用

传统的虚拟现实系统通常是基于C /OpenGL的,对硬件配置要求高、不利于网络传输,在MATLAB环境下进行调用和渲染时运算量大、实时性差.一种基于VRML虚拟现实技术和MATLAB仿真技术的虚拟试验方案,有效地解决了电传动装甲车辆动态仿真的实时性问题.运行结果表明,该方案简便可行、运行可靠,很好地满足了虚拟试验的要求,为MATLAB环境下的可视化仿真提供了一种有效方法.     

Optimal assignment of high multiplicity flight plans to dispatchers

This paper addresses the problem of finding a feasible schedule of n jobs on m parallel machines, where each job has a deadline and some jobs are preassigned to some machine. This problem arises in the daily assignment of workload to a set of flight dispatchers, and it is strongly characterized by the fact that the job lengths may assume one out of k different values, for small k. We prove the problem to be NP‐complete for k = 2 and propose an effective implicit enumeration algorithm which allows efficiently solution a set of real‐life instances. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 359–376, 2000     

Bicriteria scheduling on a single batching machine with job transportation and deterioration considerations

We study a single batching machine scheduling problem with transportation and deterioration considerations arising from steel production. A set of jobs are transported, one at a time, by a vehicle from a holding area to the single batching machine. The machine can process several jobs simultaneously as a batch. The processing time of a job will increase if the duration from the time leaving the holding area to the start of its processing exceeds a given threshold. The time needed to process a batch is the longest of the job processing times in the batch. The problem is to determine the job sequence for transportation and the job batching for processing so as to minimize the makespan and the number of batches. We study four variations (P1, P2, P3, P4) of the problem with different treatments of the two criteria. We prove that all the four variations are strongly NP‐hard and further develop polynomial time algorithms for their special cases. For each of the first three variations, we propose a heuristic algorithm and analyze its worst‐case performance. For P4, which is to find the Pareto frontier, we provide a heuristic algorithm and an exact algorithm based on branch and bound. Computational experiments show that all the heuristic algorithms perform well on randomly generated problem instances, and the exact algorithm for P4 can obtain Pareto optimal schedules for small‐scale instances. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 269–285, 2014     

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     

基于多目标的雷达组网传感器资源管理算法

在雷达组网系统的多目标跟踪过程中,当目标数量过多时,由于传感器资源不足,无法使用传统传感器的管理方法进行资源分配,且运算时间过长,不满足工程实际需求。针对以上问题,提出了一种新的多传感器多目标跟踪任务快速分配算法,该算法将跟踪目标个数和跟踪目标精度作为优化目标,首先按照设定的分配准则对传感器进行一次分配,最大化跟踪目标个数;然后利用一种基于传感器排序的启发式传感器分配方法进行二次分配,通过控制跟踪目标的协方差水平,使目标的跟踪精度尽量接近期望值。仿真结果表明,该算法能够在较短的时间内对多传感器进行有效快速地分配,既跟踪了更多的目标,又达到了期望目标的跟踪精度,并且在一定程度上控制资源消耗,减少系统的总耗能。