熵权正负理想方案灰色关联法的对地攻击目标选择

针对攻击机对地攻击的目标选择问题,提出了目标攻击优先权的计算方法,将正负理想方案与灰色关联分析方法进行融合并引进熵权的思想为各项优先权赋值,避免了权值确定过于主观的问题,提出了一种目标选择的模型,为飞行员对地攻击目标选择提供了辅助决策,具有较高的实用性。仿真结果也说明了该方法的合理性。     

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。     

Modeling and analysis of multiobjective lot splitting for N‐product M‐machine flowshop lines

Lot splitting is a new approach for improving productivity by dividing production lots into sublots. This approach enables accelerating production flow, reducing lead‐time and increasing the utilization of organization resources. Most of the lot splitting models in the literature have addressed a single objective problem, usually the makespan or flowtime objectives. Simultaneous minimization of these two objectives has rarely been addressed in the literature despite of its high relevancy to most industrial environments. This work aims at solving a multiobjective lot splitting problem for multiple products in a flowshop environment. Tight mixed‐integer linear programming (MILP) formulations for minimizing the makespan and flowtime are presented. Then, the MinMax solution, which takes both objectives into consideration, is defined and suggested as an alternative objective. By solving the MILP model, it was found that minimizing one objective results in an average loss of about 15% in the other objective. The MinMax solution, on the other hand, results in an average loss of 4.6% from the furthest objective and 2.5% from the closest objective. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

A note on combined job selection and sequencing problems

We investigate the solvability of two single‐machine scheduling problems when the objective is to identify among all job subsets with cardinality k,1≤k≤n, the one that has the minimum objective function value. For the single‐machine minimum maximum lateness problem, we conclude that the problem is solvable in O(n²) time using the proposed REMOVE algorithm. This algorithm can also be used as an alternative to Moore's algorithm to solve the minimum number of tardy jobs problem by actually solving the hierarchical problem in which the objective is to minimize the maximum lateness subject to the minimum number of tardy jobs. We then show that the REMOVE algorithm cannot be used to solve the general case of the single‐machine total‐weighted completion time problem; we derive sufficient conditions among the job parameters so that the total weighted completion time problem becomes solvable in O(n²) time. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 449–453, 2013     

Analysis of the finite‐source multiclass priority queue with an unreliable server and setup time

In this article, we study a queueing system serving multiple classes of customers. Each class has a finite‐calling population. The customers are served according to the preemptive‐resume priority policy. We assume general distributions for the service times. For each priority class, we derive the steady‐state system size distributions at departure/arrival and arbitrary time epochs. We introduce the residual augmented process completion times conditioned on the number of customers in the system to obtain the system time distribution. We then extend the model by assuming that the server is subject to operation‐independent failures upon which a repair process with random duration starts immediately. We also demonstrate how setup times, which may be required before resuming interrupted service or picking up a new customer, can be incorporated in the model. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

非周期不完全检测下的维修优化

针对gamma退化型单部件系统,基于更新和半更新过程理论建立了以期望费用率最小为目标的非周期不完全检测下的维修优化模型。利用检测规划函数使系统的检测间隔期可以依据系统的状态进行调整。为更加贴近实际,模型考虑了测量误差对维修优化的影响。通过计算可以得到最优预防性维修阈值和检测方案。给出了模型的应用算例,通过对退化速率和费用参数的灵敏度分析说明了模型的有效性。与不考虑检测误差的优化结果进行对比,证明了考虑检测误差的重要性。     

作战任务总量的迭代收敛性

为降低作战任务的复杂度,提高任务执行效率,研究了作战任务总量及其迭代收敛问题.首先,采用图形和设计结构矩阵,阐明反导作战子任务的复杂联系.再引入任务转移矩阵建立任务总量模型,总结迭代收敛条件.最后,综合考虑资源和时间约束,规划子任务优先级并优化作战资源配置.结合实例分析了任务总量迭代收敛规律的可行性和有效性,为反导作战任务规划提供了理论指导.     

Interval scheduling: A survey

In interval scheduling, not only the processing times of the jobs but also their starting times are given. This article surveys the area of interval scheduling and presents proofs of results that have been known within the community for some time. We first review the complexity and approximability of different variants of interval scheduling problems. Next, we motivate the relevance of interval scheduling problems by providing an overview of applications that have appeared in literature. Finally, we focus on algorithmic results for two important variants of interval scheduling problems. In one variant we deal with nonidentical machines: instead of each machine being continuously available, there is a given interval for each machine in which it is available. In another variant, the machines are continuously available but they are ordered, and each job has a given “maximal” machine on which it can be processed. We investigate the complexity of these problems and describe algorithms for their solution. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007