An exact branch‐and‐price algorithm for multitasking scheduling on unrelated parallel machines

We consider the multitasking scheduling problem on unrelated parallel machines to minimize the total weighted completion time. In this problem, each machine processes a set of jobs, while the processing of a selected job on a machine may be interrupted by other available jobs scheduled on the same machine but unfinished. To solve this problem, we propose an exact branch‐and‐price algorithm, where the master problem at each search node is solved by a novel column generation scheme, called in‐out column generation, to maintain the stability of the dual variables. We use a greedy heuristic to obtain a set of initial columns to start the in‐out column generation, and a hybrid strategy combining a genetic algorithm and an exact dynamic programming algorithm to solve the pricing subproblems approximately and exactly, respectively. Using randomly generated data, we conduct numerical studies to evaluate the performance of the proposed solution approach. We also examine the effects of multitasking on the scheduling outcomes, with which the decision maker can justify making investments to adopt or avoid multitasking.     

基于随机搜索策略的中继卫星调度方法

高质量的调度方案不仅能满足用户的需求,还能为中继卫星系统的计划编制提供科学的决策手段和依据。针对日益多样化的用户需求,采用全新的中继卫星调度应用模式,允许用户提交多个可以滑动的时间窗口。面向这种调度模式,考虑中继业务中任务调度的灵活性和任务间的冲突,构建考虑多滑动窗口的中继卫星调度模型,并设计基于随机搜索策略的中继卫星调度算法。算法包括任务资源匹配与邻域生成、可用时间段生成、任务冲突分析、邻域搜索与冲突消解以及资源与任务集更新5个算子。通过仿真实验将该算法与基于时间自由度的启发式算法进行对比,验证了算法的有效性。     

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.     

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.     

一种用于SpaceWire网络的混合路由机制设计*

针对星上系统总线多元性导致的星载网络接口和协议不能标准化的发展瓶颈,本文基于SpaceWire总线协议,通过将静态路由(时间触发)与动态路由(事件触发)机制结合,实现了控制数据和载荷数据共用网络。静态路由完全遵循SpaceWire-D协议,在保证确定性传输的同时,通过启发式调度算法首次实现了多时间窗并行调度,并提出利用最大公约数法设计时间窗,以提高网络吞吐量;动态路由通过对随机事件和载荷数据分配优先级,实现传输路径冲突时对紧急任务的优先处理。最后在OPENT中搭建网络系统仿真模型,对所提出的路由机制进行了仿真。实验结果表明,静态路由时段网络吞吐量较现有调度算法有明显提高,动态路由实现了紧急事件优先传输。     

集中控制混合网络中基于流的资源分配算法

集中控制混合网络中,异构化网络内部的流量具有一定的规律和特性,如果使用原有的单一的离散式最大极值和无状态的网络资源调度算法,忽略了异构网络规律,会造成网络利用率较低、易震荡、部分网络流延迟等问题。通过分析由集中控制网络和普通网络组成的混合网络的拓扑结构,对混合网络结构中常见问题如流闪现、不能估计的流、路径堵塞或连接震荡场景进行分析,并提出基于期望和状态的流量评价资源规划算法POS和POS-FME。算法考虑混合网络的运行状态,对系统可用资源进行评估,为系统中各种流匹配对应可用资源,并具有一定的预测作用,从而避免混合网络出现运行效率低下的场景。通过实验,POS算法和POS-FME算法相对传统算法,利用率提高了10%～30%,并降低了震荡和平均延迟。     

带有活动收益不确定特征的成像侦察卫星调度问题

根据区域目标的侦察需求,研究了面向区域目标的多星调度问题。分析了调度问题中活动收益不确定特征,讨论了活动收益的上下界。针对收益不确定的特点,设计了影响力指标用于评估活动对调度方案的影响。基于活动影响力与执行时间设计了一种带局部诱导的禁忌搜索算法,采用分层次的、变评价函数机制引导求解过程趋向多目标优化,在优先提高覆盖率的同时兼顾减少资源消耗。最后,以算例验证了算法的有效性,并通过方案比较说明算法具有较好的寻优能力。     

海上编队传感器管理架构研究

在信息化海战场,获取信息优势是保障作战胜利的基础之一,海上编队传感器管理是提升传感器探测整体效能,从而达成信息优势的关键环节.首先分析了海上编队传感器管理需求,包括组成结构、作用以及编队、平台、传感器各层级的管理需求;其次研究了海上编队传感器管理的总体架构,提出采用混合式的体系结构,设计了事前规划与实时调度2个方面的处...     

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