基于Monte Carlo方法的一对二马尔可夫随机格斗模型

讨论了一对二马尔可夫随机格斗双方获胜概率计算问题。提出了一种新颖的一对二马尔可夫随机格斗任意对抗回合双方获胜概率的计算方法,该方法首先基于Monte Carlo仿真计算各个对抗回合中双方发射次序的概率分布,再利用全概率公式确定马尔可夫链的状态转移概率矩阵,从而克服了马尔可夫随机格斗模型往往只能提供无限对抗回合之后格斗双方获胜概率的缺点,为运用马尔可夫随机格斗研究火力运用和弹药分配提供了新途径,并用实例说明了该方法的有效性。     

大数据时代方法理论研究初探

当前对于大数据时代的到来并无太大争议。但是,对于大数据方法理论的研究,仍处于起步阶段。作为重“利”轻“理”的商业领域,主要任务是从大数据价值挖掘中获利。虽然有人从商业创新、思维创新、科技创新和社会透明等角度,阐述了对大数据问题的认识,但并未将认识上升到一般研究的方法理论层面。这就出现了一种矛盾——虽然提出了“大数据时代”,但是并未给这个时代提供普遍意义上的大数据研究方法理论。     

计算机“二一十”进制数据转换算法

“二一十”转换是计算机中经常用到的,将二进制浮点数0.B_1B_2…B_n*2~B转换成十进制数0.D_1D_2…D_n*10~D的关键是首先求出D。本文通过全面研制二进制浮点数的性质,推导出了一个关于精确求D的重要结论,并由此构造出一个实际应用时总误差最小的高效求D公式。     

Scheduling and due‐date quotation in a make‐to‐order supply chain

We consider a manufacturer, served by a single supplier, who has to quote due dates to arriving customers in a make‐to‐order production environment. The manufacturer is penalized for long lead times and for missing due dates. To meet due dates, the manufacturer has to obtain components from a supplier. We model this manufacturer and supplier as a two‐machine flow shop, consider several variations of this problem, and design effective due‐date quotation and scheduling algorithms for centralized and decentralized versions of the model. We perform extensive computational testing to assess the effectiveness of our algorithms and to compare the centralized and decentralized models to quantify the value of centralized control in a make‐to‐order supply chain. Since complete information exchange and centralized control is not always practical or cost‐effective, we explore the value of partial information exchange for this system. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

基于ADUC831的坦克火控系统控制盒的改进

用功能强大的ADUC831芯片代替原控制盒的87C51芯片,为引入各种先进算法,改进坦克炮控系统的控制品质,打下了软硬件基础。新系统用C语言编程,简化硬件设计,实现与上位机通信,便于数据采集、在线参数调试和性能分析。     

A bicriterion approach to common flow allowances due window assignment and scheduling with controllable processing times

We investigate a single‐machine scheduling problem for which both the job processing times and due windows are decision variables to be determined by the decision maker. The job processing times are controllable as a linear or convex function of the amount of a common continuously divisible resource allocated to the jobs, where the resource allocated to the jobs can be used in discrete or continuous quantities. We use the common flow allowances due window assignment method to assign due windows to the jobs. We consider two performance criteria: (i) the total weighted number of early and tardy jobs plus the weighted due window assignment cost, and (ii) the resource consumption cost. For each resource consumption function, the objective is to minimize the first criterion, while keeping the value of the second criterion no greater than a given limit. We analyze the computational complexity, devise pseudo‐polynomial dynamic programming solution algorithms, and provide fully polynomial‐time approximation schemes and an enhanced volume algorithm to find high‐quality solutions quickly for the considered problems. We conduct extensive numerical studies to assess the performance of the algorithms. The computational results show that the proposed algorithms are very efficient in finding optimal or near‐optimal solutions. © 2017 Wiley Periodicals, Inc. Naval Research Logistics, 64: 41–63, 2017     

Due‐window assignment with unit processing‐time jobs

In due‐window assignment problems, jobs completed within a designated time interval are regarded as being on time, whereas early and tardy jobs are penalized. The objective is to determine the location and size of the due‐window, as well as the job schedule. We address a common due‐window assignment problem on parallel identical machines with unit processing time jobs. We show that the number of candidate values for the optimal due‐window starting time and for the optimal due‐window completion time are bounded by 2. We also prove that the starting time of the first job on each of the machines is either 0 or 1, thus introducing a fairly simple, constant‐time solution for the problem. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Multiple common due dates

Common due date problems have been extensively discussed in the scheduling literature. Initially, these problems discussed finding a common due date for a set of jobs on a single machine. These single machine problems were later extended to finding the common due date on a set of parallel machines. This paper further extends the single machine problem to finding multiple common due dates on a single machine. For a basic and important class of penalty functions, we show that this problem is comparable to the parallel machine problem. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 293–298, 2001     

Delivery‐date and capacity management in a decentralized internal market

We study competitive due‐date and capacity management between the marketing and engineering divisions within an engineer‐to‐order (ETO) firm. Marketing interacts directly with the customers and quotes due‐dates for their orders. Engineering is primarily concerned with the efficient utilization of resources and is willing to increase capacity if the cost is compensated. The two divisions share the responsibility for timely delivery of the jobs. We model the interaction between marketing and engineering as a Nash game and investigate the effect of internal competition on the equilibrium decisions. We observe that the internal competition not only degrades the firm's overall profitability but also the serviceability. Finally, we extend our analysis to multiple‐job settings that consider both flexible and inflexible capacity. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008