导航卫星上行注入任务调度模型及启发式算法

合理安排导航卫星与地面上注站星地链路构建与导航电文上注,对保证星上导航电文的准确性和精确性有着重要意义。对卫星导航系统上行注入过程进行了分析,构建了上行注入任务调度问题的多目标混合整数规划模型,设计了基于规则的启发式求解算法。基于北斗二代和美国的GPS卫星导航系统构建仿真场景,仿真结果验证了模型和算法的正确性、可行性;通过分析仿真结果,得到影响卫星导航系统上行注入任务完成的关键因素。     

舰艇防空火力规划与调度方法研究

根据舰艇防空武器拦截过程的时间连续性和拦截效果的不确定性特点,提出了智能规划和优化调度相结合的舰艇防空计划生成方法。在规划阶段,先用智能规划描述语言PDDL对舰艇防空问题进行建模;针对新的来袭目标或观察的拦截结果,利用智能规划的高效行动推理能力,快速生成可能的备选行动方案;在优化调度阶段,对已生成的备选方案的行动系列进行时间、资源冲突处理,并计算选择出当前最佳拦截方案。与现有的采用离散化处理的武器-目标分配方法相比,该规划与调度过程充分体现了拦截过程的连续性,拦截效果的不确定性,拦截过程中的武器协同,以及最佳拦截时机的选择等,更好地描述了舰艇防空的实际过程。最后,通过蒙特卡罗仿真试验,验证了算法的有效性,为舰艇的自动化防空提供了一种新的解决办法。     

基于信息损失最小的预警卫星传感器调度模型

科学合理地调度预警卫星传感器资源是提高弹道导弹预警作战效能的重要手段.在预警卫星传感器资源(主要是凝视探测器)有限而进攻弹道导弹目标数量较多时,利用最小信息损失准则,将传感器调度问题转化为最优访问路径问题进行建模研究,满足了导弹预警资源调度的需要,仿真结果验证了模型的可靠性和可用性.     

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     

基于空间约束的舰载机出库调度

舰载机在航母上的调度问题是制约舰载机出动和回收的重要因素,以往研究主要集中在飞行甲板调度方面。针对舰载机在航母上的出入库问题进行研究,着力解决舰载机在航母上二、三波次的出动能力。首先对舰载机出库的流程进行分析,梳理制约因素。其次,应用柔性流水车间调度理论对空间约束条件下的舰载机出库调度问题进行建模。再次,对智能粒子群算法应用于舰载机出库调度问题进行分析,对编码进行设计,并给出算法流程。最后,对出库流程进行仿真,计算出最优出库方案及时间,验证了模型的准确性。     

Evaluating appointment postponement in scheduling patients at a diagnostic clinic

Diagnostic clinics are among healthcare facilities that suffer from long waiting times which can worsen medical outcomes and increase patient no-shows. Reducing waiting times without significant capital investments is a challenging task. We tackle this challenge by proposing a new appointment scheduling policy that does not require significant investments for diagnostic clinics. The clinic in our study serves outpatients, inpatients, and emergency patients. Emergency patients must be seen on arrival, and inpatients must be given next day appointments. Outpatients, however, can be given later appointments. The proposed policy takes advantage of this by allowing the postponement of the acceptance of appointment requests from outpatients. The appointment scheduling process is modeled as a two-stage stochastic programming problem where a portion of the clinic capacity is allocated to inpatients and emergency patients in the first stage. In the second stage, outpatients are scheduled based on their priority classes. After a detailed analysis of the solutions obtained from the two-stage stochastic model, we develop a simple, non-anticipative policy for patient scheduling. We evaluate the performance of this proposed, easy-to-implement policy in a simulation study which shows significant improvements in outpatient indirect waiting times.     

Scheduling twin robots on a line

This article introduces the twin robots scheduling problem (TRSP), in which two robots positioned at the opposite ends of a rail are required to deliver items to positions along the rail, and the objective is to minimize the makespan. A proof of ‐hardness of the TRSP is presented, along with exact and heuristic algorithms. Computational results on challenging instances are provided.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 119–130, 2014     

Maintenance scheduling for modular systems: Modeling and algorithms

We study new models of scheduled maintenance management for modular systems, consisting of multiple components with respective cycle limits. The cycle limit of each component specifies the time interval in which this component must be repaired or replaced. The goal is to compute a feasible maintenance schedule that minimizes the cost associated with component maintenance. Applications of these models arise in Air Force aircraft maintenance as well as in other arenas with required preventive maintenance. The typical cost structures that arise in practical settings are submodular, which make the resulting models computationally challenging. We develop two efficient and operationally tenable approximation algorithms. We prove constant factor worst‐case guarantees for both algorithms, and present computational experiments showing that these algorithms perform within a few percent of optimality on operationally relevant instances. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 472–488, 2014     

一种装甲车辆CAN总线混合调度算法

针对当前装甲车辆综合电子系统节点消息传输不公平、紧急消息传输不及时等缺点,结合某型车辆消息紧急度和截止期,按照分层处理原则对总线协议进行了改进,提出了"分级决策动态均衡"的混合调度算法,并通过试验验证了算法的可行性和有效性。     

超声兰姆波在储罐底部传播的数值模拟研究

选择仅有切向位移分量的S2超声兰姆波模式,分别对其在自由单层钢板、有罐壁但无液体负载的单层钢板和有罐壁且有液体负载的单层钢板中的传播规律进行了数值模拟研究.计算结果表明,尽管罐壁和液体负载对超声兰姆波的传播行为产生了一定程度的影响,但仍可保证S2超声兰姆波模式的时域脉冲信号传播较远的距离.研究结果为采用超声兰姆波检测储...