A non-myopic scheduling method of radar sensors for maneuvering target tracking and radiation control

In decades, the battlefield environment is becoming more and more complex with plenty of electronic equipments. Thus, in order to improve the survivability of radar sensors and satisfy the requirement of maneuvering target tracking with a low probability of intercept, a non-myopic scheduling is proposed to minimize the radiation cost with tracking accuracy constraint. At first, the scheduling problem is formulated as a partially observable Markov decision process (POMDP). Then the tracking accuracy and radiation cost over the future finite time horizon are predicted by the posterior carmér-rao lower bound (PCRLB) and the hidden Markov model filter, respectively. Finally, the proposed scheduling is implemented efficiently by utilizing the branch and bound (B&B) pruning algorithm. Simulation results show that the performance of maneuvering target tracking was improved by the improved interacting multiple model (IMM), and the scheduler time and maximum memory consumption were significant reduced by the present B&B pruning algorithm without losing the optimal solution.     

The prediction formula and a risk-based sensor scheduling method in target detection with guiding information

Sensor scheduling is used to improve the sensing performance in the estimation of targets' states. However, few papers are on the sensor scheduling for target detection with guiding information. This letter can remedy this deficiency. A risk-based target detection method with guiding information is provided firstly, based on which, the sensor scheduling approach is aiming at reducing the risk and uncertainty in target detection, namely risk-based sensor scheduling method. What should be stressed is that the Prediction Formula in sensor scheduling is proposed. Lastly, some examples are conducted to stress the effectiveness of this proposed method.     

Two‐machine flow shop scheduling with common due window to minimize weighted number of early and tardy jobs

This article studies two due window scheduling problems to minimize the weighted number of early and tardy jobs in a two‐machine flow shop, where the window size is externally determined. These new scheduling models have many practical applications in real life. However, results on these problems have rarely appeared in the literature because of a lack of structural and optimality properties for solving them. In this article, we derive several dominance properties and theorems, including elimination rules and sequencing rules based on Johnsos order, lower bounds on the penalty, and upper bounds on the window location, which help to significantly trim the search space for the problems. We further show that the problems are NP‐hard in the ordinary sense only. We finally develop efficient pseudopolynomial dynamic programming algorithms for solving the problems. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

Capacitated lot‐sizing and scheduling with parallel machines,back‐orders,and setup carry‐over

We address the capacitated lot‐sizing and scheduling problem with setup times, setup carry‐over, back‐orders, and parallel machines as it appears in a semiconductor assembly facility. The problem can be formulated as an extension of the capacitated lot‐sizing problem with linked lot‐sizes (CLSPL). We present a mixed integer (MIP) formulation of the problem and a new solution procedure. The solution procedure is based on a novel “aggregate model,” which uses integer instead of binary variables. The model is embedded in a period‐by‐period heuristic and is solved to optimality or near‐optimality in each iteration using standard procedures (CPLEX). A subsequent scheduling routine loads and sequences the products on the parallel machines. Six variants of the heuristic are presented and tested in an extensive computational study. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

面向点及区域目标的遥感卫星任务调度

遥感应用需求中存在点目标和区域目标两类任务,遥感卫星对两类任务的调度方式存在很大区别,将二者统一调度困难.本文将点目标视为特殊的区域目标,将它们按照卫星观测机会分解,构建元任务,将两类目标在元任务层次进行统一;根据任务类型分别构建收益函数,兼顾了二者在收益计算上的差异,并建立了面向点及区域目标的遥感卫星任务调度模型,实现了对两类任务的综合调度.仿真实例证明,此方法能够提高卫星的观测效率.     

支持并行工程的造船分段作业计划系统

针对传统造船模式下,车间作业计划与工艺设计串行工作方式的缺点,基于并行工程的原理,提出了分段作业计划与工艺设计的集成运行模式,为实现造船CAPP系统与PPC系统的集成化和并行化提供了实现的基础。针对集成模式的特点,建立了分段作业计划系统资源优化的数学模型,应用遗传算法解决了针对任意分段装配工艺方案的多资源平衡优化问题,可以得到每项作业最优的开工时间,同时能够给出多种资源的最优分布结果,满足了多工艺方案之间资源利用率的比较。最后,给出了计算实例,计算机模拟结果说明了这一方法的有效性。     

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。     

匈牙利算法在多目标分配中的应用

在多目标攻击决策中 ,根据 Harold提出的目标优势函数 ,分析了使所有目标机的总优势函数为指派问题 ,运用匈牙利算法对 n对 n的最优目标分配指派问题进行求解 ,并把它推广至 n对 m的多目标分配中。仿真结果表明匈牙利算法对于此类多目标分配指派问题的求解是十分有效的。     

基于预定作业周期的航母作战部署调度研究

为科学筹划航母作战部署调度,优化航母作战兵力的运用,对航母作战部署调度问题进行建模研究。介绍航母预定作业周期,重点阐述航母综合训练期、维修保障期和人员/作战节奏等相关内容;在此基础上,分析航母作战部署调度的约束条件,在满足对作战区域有效时间覆盖条件下,以最小化航母作战兵力数量为目标函数,构建航母作战部署调度优化模型,并通过实例进行验证。结果表明,该模型是有效、实用的,可为科学决策航母作战部署调度提供依据和方法。     

天基预警系统资源调度方法

对面向导弹预警任务的天基预警系统中的低轨卫星资源调度问题进行了研究.对预警任务的特性进行分析,提出了一种预警任务规划与分解方法以减少任务对资源占用时间的需求;在此基础上建立了该问题的约束满足CSP调度模型;针对该模型变量多、解空间规模庞大的特点以及对求解算法时效性的要求,设计了一种基于局部解空间跳出机制的改进型遗传算法MGA.仿真表明该模型与算法在给定时间内能够得到满意的调度方案.