Sequential and systematic sampling plans for the Markov‐dependent production process

Acceptance sampling plans are used to assess the quality of an ongoing production process, in addition to the lot acceptance. In this paper, we consider sampling inspection plans for monitoring the Markov‐dependent production process. We construct sequential plans that satisfy the usual probability requirements at acceptable quality level and rejectable quality level and, in addition, possess the minimum average sample number under semicurtailed inspection. As these plans result in large sample sizes, especially when the serial correlation is high, we suggest new plans called “systematic sampling plans.” The minimum average sample number systematic plans that satisfy the probability requirements are constructed. Our algorithm uses some simple recurrence relations to compute the required acceptance probabilities. The optimal systematic plans require much smaller sample sizes and acceptance numbers, compared to the sequential plans. However, they need larger production runs to make a decision. Tables for choosing appropriate sequential and systematic plans are provided. The problem of selecting the best systematic sampling plan is also addressed. The operating characteristic curves of some of the sequential and the systematic plans are compared, and are observed to be almost identical. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 451–467, 2001     

一类对固定目标的集群搜寻对策问题及求解

利用集群搜索对策的理论与方法 ,建立了集群对固定目标的一类搜索对策模型 ,给出了集群的ε -最优搜寻策略 ,并考虑了其在搜索过程中的应用     

Rendezvous of three agents on the line

This paper considers a three‐person rendezvous problem on the line which was introduced earlier by the authors. Three agents are placed at three consecutive integer value points on the real line, say 1, 2, and 3. Each agent is randomly faced towards the right or left. Agents are blind and have a maximum speed of 1. Their common aim is to gather at a common location as quickly as possible. The main result is the proof that a strategy given by V. Baston is the unique minimax strategy. Baston's strategy ensures a three way rendezvous in time at most 3.5 for any of the 3!2³ = 48 possible initial configurations corresponding to positions and directions of each agent. A connection is established between the above rendezvous problem and a search problem of L. Thomas in which two parents search separately to find their lost child and then meet again. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 244–255, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10005     

Rendezvous search on labeled networks

Two players are independently placed on a commonly labelled network X. They cannot see each other but wish to meet in least expected time. We consider continuous and discrete versions, in which they may move at unit speed or between adjacent distinct nodes, respectively. There are two versions of the problem (asymmetric or symmetric), depending on whether or not we allow the players to use different strategies. After obtaining some optimality conditions for general networks, we specialize to the interval and circle networks. In the first setting, we extend the work of J. V. Howard; in the second we prove a conjecture concerning the optimal symmetric strategy. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 256–274, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10011     

Continuous accumulation games on discrete locations

In an accumulation game, a HIDER attempts to accumulate a certain number of objects or a certain quantity of material before a certain time, and a SEEKER attempts to prevent this. In a continuous accumulation game the HIDER can pile material either at locations $1, 2, …, n, or over a region in space. The HIDER will win (payoff 1) it if accumulates N units of material before a given time, and the goal of the SEEKER will win (payoff 0) otherwise. We assume the HIDER can place continuous material such as fuel at discrete locations i = 1, 2, …, n, and the game is played in discrete time. At each time k > 0 the HIDER acquires h units of material and can distribute it among all of the locations. At the same time, k, the SEEKER can search a certain number s < n of the locations, and will confiscate (or destroy) all material found. After explicitly describing what we mean by a continuous accumulation game on discrete locations, we prove a theorem that gives a condition under which the HIDER can always win by using a uniform distribution at each stage of the game. When this condition does not hold, special cases and examples show that the resulting game becomes complicated even when played only for a single stage. We reduce the single stage game to an optimization problem, and also obtain some partial results on its solution. We also consider accumulation games where the locations are arranged in either a circle or in a line segment and the SEEKER must search a series of adjacent locations. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 60–77, 2002; DOI 10.1002/nav.1048     

Adaptive random search for continuous simulation optimization

We present, analyze, and compare three random search methods for solving stochastic optimization problems with uncountable feasible regions. Our adaptive search with resampling (ASR) approach is a framework for designing provably convergent algorithms that are adaptive and may consequently involve local search. The deterministic and stochastic shrinking ball (DSB and SSB) approaches are also convergent, but they are based on pure random search with the only difference being the estimator of the optimal solution [the DSB method was originally proposed and analyzed by Baumert and Smith]. The three methods use different techniques to reduce the effects of noise in the estimated objective function values. Our ASR method achieves this goal through resampling of already sampled points, whereas the DSB and SSB approaches address it by averaging observations in balls that shrink with time. We present conditions under which the three methods are convergent, both in probability and almost surely, and provide a limited computational study aimed at comparing the methods. Although further investigation is needed, our numerical results suggest that the ASR approach is promising, especially for difficult problems where the probability of identifying good solutions using pure random search is small. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

考虑随机回放的卫星数传调度问题的一种求解方法

针对考虑随机回放的卫星数传调度问题,从置换空间到调度解空间的映射方法和置换空间的搜索算法两方面进行了研究.提出了一种时间窗优先的置换序列映射算法,并证明该映射算法可以将置换序列映射到调度解空间上的最优解.提出了一种遗传随机搜索算法,基于有记忆功能的随机邻域搜索,在置换空间上搜索产生优化调度的置换序列.仿真计算表明,遗传随机搜索算法可以增强遗传算法的局部搜索能力,在搜索结果上平均获得了2.72%的改进.     

专题式Web信息检索系统的设计与实现

主要介绍WIRSOS (Webinformationretrievalsystemforordnancesupport)系统设计与实现的关键技术。本系统采用搜索引擎技术 ,利用网络机器人 (WebRobot)采集WWW上信息 ,通过对整篇文档的分词处理和相似性计算 ,针对某一专题信息进行收集 ,从而提高检索效率和精度     

C3I系统体系结构的演化开发过程

体系结构的建立是C3I系统工程的重要组成部分,它是保障所开发的C3I系统满足军事需求的机制.提出了C3I系统体系结构的演化开发过程,它是体系结构开发在需求汇集、体系结构设计、建立可执行模型、体系结构评价等四个主要任务区域中循环迭代、逐步求精的过程.确定和论述了演化开发过程中各任务区域的主要活动.     

文章编号：基于多目标进化搜索算法的AUV地磁仿生导航方法

针对水下自主航行器(AUV)地磁多参量多目标搜索的问题,提出了一种基于磁趋势敏感的多目标进化搜索算法。在进化算法的结构下,利用地磁场参量与导航路径的约束关系,以磁趋势敏感作为后验评估准则,建立导航模型,使得地磁多分量伴随航行器的运动同时同地收敛至各自目标值,实现导航目的。通过与六边形路径搜索算法的仿真对比,验证了多目标进化搜索算法的有效性和优越性。