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     

一类具有时滞的病毒动力学模型分析

研究一类具有时滞的病毒动力学模型。研究了系统解的有界性;讨论了各个非负平衡点的局部稳定性,应用比较定理得到了各非负平衡点全局渐近稳定的充分条件。     

贪心遗传算法解决一般武器-目标分配问题

一般武器-目标分配问题,是使武器发挥最大效能而使目标遭受最大毁伤的最优化问题.遗传算法广泛用于解决最优化问题.提出一种具有贪心优化机制的局部搜索方法,以提高遗传算法的搜索效率,从而迅速找到全局最优解.应用于炮兵武器-目标分配问题的仿真试验结果表明,此算法比现有的其他搜寻算法具有更好的求解效率.     

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.     

修订地方性消防法规需要审视的几个关系

随着消防法的修订颁布,目前各地适用的地方性消防法规的相关规定已经不适应新形势下消防法制建设的需要,亟待重新修订。通过对消防法、相关法律以及部门消防规章与地方性消防法规之间关系的审视和分析,为地方性消防法规的修订提供参考。     

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     

特殊半鞅的强大数定律

利用特殊半鞅的收敛定理和一般形式的Kronecker引理,给出了特殊半鞅和非负特殊半鞅强大数定律的一般形式,推广和完善了已有的结果.     

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。     

地磁仿生导航的多目标进化搜索算法

针对水下自主航行器地磁多参量多目标搜索的问题,提出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。