Scheduling with centralized and decentralized batching policies in concurrent open shops

This article considers batch scheduling with centralized and decentralized decisions. The context of our study is concurrent open shop scheduling where the jobs are to be processed on a set of independent dedicated machines, which process designated operations of the jobs in batches. The batching policy across the machines can be centralized or decentralized. We study such scheduling problems with the objectives of minimizing the maximum lateness, weighted number of tardy jobs, and total weighted completion time, when the job sequence is determined in advance. We present polynomial time dynamic programming algorithms for some cases of these problems and pseudo‐polynomial time algorithms for some problems that are NP‐hard in the ordinary sense. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 58: 17–27, 2011     

一种简单有效的处理冲突证据的D-S改进方法*

D-S证据理论在决策级信息融合领域有着广泛的应用,但其在合成冲突证据时会出现与直观结论不符的现象。通过深入分析D-S证据理论合成冲突证据时的失效原因,提出了一种简单有效的改进方法。通过主观权重和客观权重的综合得到不同证据的信任度,以此确定冲突证据及对应的折扣度并对其进行折扣度修正,使合成结果快速向正确类型收敛。仿真结果表明,同已有方法相比,本文方法特别适合具有少数冲突证据的情况,其合成结果更加符合直观判断。     

应用型本科高校课程改革：目标、体系改革探索

课程改革已成为当前我国教育改革应用型本科类高校教学改革的核心。本文基于实践视角,将应用型本科高校的课程改革聚焦在厘清培养目标定位,构建服务于培养目标的课程体系和变革教学方法上,并结合部分应用型本科高校跨越式发展定位,就应用型本科大学的课程改革策略进行初步探讨。     

Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times

We study a stochastic outpatient appointment scheduling problem (SOASP) in which we need to design a schedule and an adaptive rescheduling (i.e., resequencing or declining) policy for a set of patients. Each patient has a known type and associated probability distributions of random service duration and random arrival time. Finding a provably optimal solution to this problem requires solving a multistage stochastic mixed‐integer program (MSMIP) with a schedule optimization problem solved at each stage, determining the optimal rescheduling policy over the various random service durations and arrival times. In recognition that this MSMIP is intractable, we first consider a two‐stage model (TSM) that relaxes the nonanticipativity constraints of MSMIP and so yields a lower bound. Second, we derive a set of valid inequalities to strengthen and improve the solvability of the TSM formulation. Third, we obtain an upper bound for the MSMIP by solving the TSM under the feasible (and easily implementable) appointment order (AO) policy, which requires that patients are served in the order of their scheduled appointments, independent of their actual arrival times. Fourth, we propose a Monte Carlo approach to evaluate the relative gap between the MSMIP upper and lower bounds. Finally, in a series of numerical experiments, we show that these two bounds are very close in a wide range of SOASP instances, demonstrating the near‐optimality of the AO policy. We also identify parameter settings that result in a large gap in between these two bounds. Accordingly, we propose an alternative policy based on neighbor‐swapping. We demonstrate that this alternative policy leads to a much tighter upper bound and significantly shrinks the gap.     

利用混合编程改善SMP机群上并行矩阵乘法的性能

针对SMP机群,探讨了分别利用单机优化、OpenMP与MPI从指令级、共享存储级与分布主存级三个层次上改善矩阵并行乘Fox算法性能的方法。并通过调用数学函数库与混合编程的方式,在深腾6800上进行了实验,取得了相当满意的数值效果。     

面向对象的反舰导弹航路规划

针对反舰导弹航路规划的任务特点,提出了一种面向对象的反舰导弹航路规划方法.在全面分析了反舰导弹航路规划中可能用到的类的基础上,建立了对各种类的描述,使得不同算法和不同任务要求的航路规划可以通过对类的继承和对成员函数的重载实现.最后,在VC 平台下,对这种面向对象的反舰导弹航路规划方法进行了编程实验.     

Optimal maintenance policies for serial,multi‐machine systems with non‐instantaneous repairs

We study optimal age‐replacement policies for machines in series with non‐instantaneous repair times by formulating two nonlinear programs: one that minimizes total cost‐rate subject to a steady‐state throughput requirement and another that maximizes steady‐state throughput subject to a cost‐rate budget constraint. Under reasonable assumptions, the single‐machine cost‐optimal and throughput‐optimal solutions are unique and orderable, and the multi‐machine optimal solutions have appealing structure. Furthermore, we establish equivalence between the two formulations and provide an illustrative numerical example. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

面向决策的一体化建模方法及其在兵力筹划中的应用

在对军事决策问题的主要特点进行分析的基础上,提出从军事概念模型到数学模型再到定性推理模型的一体化建模思想.以空军航空兵遂行直接航空火力支援任务为想定背景,根据EATI模板,利用基于UML的Rose工具依次对想定任务的实体、任务、交互等进行分析;对于兵力筹划中的结构化问题建立了机会约束多目标规划数学模型;对于非结构化问题则构造了推理机,推理机体现了定量与定性相结合的决策分析思想.最后,以一个实例验证文章思路的可行性.     

新型多目标遗传算法及其在导弹射击效能优化中的应用

多目标规划是一类重要的优化模型,有着广泛的实际应用,但其求解至今仍是运筹学的一个难点.针对一般约束多目标优化问题,在设计了新的适应度函数和选择算子的基础上,提出一种新型多目标遗传算法.将其应用于导弹对集群目标射击效能优化问题,验证了算法的有效性.     

战时装备调配保障决策模型构建研究

分析了战时装备调配保障决策的特点,运用模糊聚类分析法对装备调配保障对象进行了分组和优先级排序,以此为基础,运用目标规划法构建了战时装备调配保障决策模型,最后,通过实例验证了模型的可行性和有效性．