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.     

动圈式永磁直线直流电机的精英保留多种群遗传优化算法

为了实现陆基无人机电磁弹射器高机动性及其直线弹射电机的高功率密度,针对动圈式永磁直线直流电机,提出精英保留的多种群遗传算法(Multi-Population Genetic Algorithm with Elite Retention, MPGAER)的电机最大功率密度优化方法。以磁通密度和电流密度为约束条件,利用其搜索能力强、收敛速度快的特点优化电机的结构参数,并与磁路法初始设计结果和传统遗传算法优化结果进行比较。结果表明:与磁路法初始设计相比,MPGAER能使电机质量减少6.25%,功率密度提高10%,电机动态性能得到提高;MPGAER优化设计的电机功率密度高于遗传算法设计结果,所提方法有效地解决了在优化过程中出现易收敛于局部最优点和寻优效果差的问题。     

动初级高速六相直线感应电机工作特性分析

为了准确刻画对象模型,采用一阶等效电路瞬态涡流分析法对动态边端效应影响下动初级高速六相直线感应电机的参数时变规律进行了定量计算,并通过感应涡流损耗推导得到考虑动态边端效应时电机的等效电路。基于此,通过电磁推力计算及效率评估对动态边端效应影响下电机的工作特性进行了详细分析。利用不同运行速度条件下的有限元仿真及动态实验验证了理论分析和推导的正确性。     

Higher‐order Markov chain models for categorical data sequences*

In this paper we study higher‐order Markov chain models for analyzing categorical data sequences. We propose an efficient estimation method for the model parameters. Data sequences such as DNA and sales demand are used to illustrate the predicting power of our proposed models. In particular, we apply the developed higher‐order Markov chain model to the server logs data. The objective here is to model the users' behavior in accessing information and to predict their behavior in the future. Our tests are based on a realistic web log and our model shows an improvement in prediction. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Index policies for the routing of background jobs

Arriving (generic) jobs may be processed at one of several service stations, but only when no other (dedicated) jobs are waiting there. We consider the problem of how to route these incoming background jobs to make best use of the spare service capacity available at the stations. We develop an approximative approach to Whittle's proposal for restless bandits to obtain an index policy for routing. The indices concerned are increasing and nonlinear in the station workload. A numerical study testifies to the strong performance of the index policies developed. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

基于线阵CCD的弹丸图像处理

分析了线阵CCD测弹丸攻角的原理,研究了线阵CCD在弹丸动态测试中的整体图像处理方法,提出一种新的方法:帧相减、局部归一化、二维自适应除噪滤波器和两重阈值复合算法的综合。该方法对复杂环境下的动态CCD图像处理特别有效。     

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     

针对AES密码第1轮线性碰撞的代数攻击

将旁路攻击中线性碰撞思想与代数攻击方法相结合,使AES加密操作第1轮中的碰撞转换为线性方程组,构造了SAT求解器求解方程组,利用穷举攻击筛选真实的密钥。实验结果表明,该方法可降低密钥搜索空间,最终获得AES128位真实密钥,攻击效果优于碰撞攻击。     

New heuristic methods for the capacitated multi‐facility Weber problem

In this paper we consider the capacitated multi‐facility Weber problem with the Euclidean, squared Euclidean, and ?_p‐distances. This problem is concerned with locating m capacitated facilities in the Euclidean plane to satisfy the demand of n customers with the minimum total transportation cost. The demand and location of each customer are known a priori and the transportation cost between customers and facilities is proportional to the distance between them. We first present a mixed integer linear programming approximation of the problem. We then propose new heuristic solution methods based on this approximation. Computational results on benchmark instances indicate that the new methods are both accurate and efficient. © 2006 Wiley Periodicals, Inc. Naval Research Logistics 2006     

基于SDP松弛的干扰资源优化分配技术研究

提出一种基于semidefinite programming(简称SDP)松弛的干扰资源优化分配算法。在问题优化过程中首先对模型中非凸的约束条件进行松弛,变为凸约束,将原来的数学模型转化成SDP求解形式,利用内点算法对松弛后的模型求解。该算法利用解析的手段使得干扰资源优化分配问题中的NP难问题在多项式时间内得以解决,并且有较高的可靠性。仿真结果验证了算法的有效性。