基于粒子群优化的稀疏分解最优匹配原子搜索算法

信号的稀疏分解能得到信号的稀疏表示形式,便于进一步处理,但其计算非常复杂,是一个NP问题.粒子群优化是群体智能优化算法,算法简单,易于实现,且搜索效果好.把粒子群优化算法用于稀疏分解的最优匹配原子的搜索,能降低稀疏分解复杂度,同时减少稀疏分解的超完备字典对存储空间的占用,以提高用稀疏分解理论进行信号处理的计算效率,满足或接近实时性的要求.实验证明,此方法切实可行.     

Analysis of a machine repair problem with an unreliable server and phase type repairs and services

In this paper we study a machine repair problem in which a single unreliable server maintains N identical machines. The breakdown times of the machines are assumed to follow an exponential distribution. The server is subject to failure and the failure times are exponentially distributed. The repair times of the machine and the service times of the repairman are assumed to be of phase type. Using matrix‐analytic methods, we perform steady state analysis of this model. The time spent by a failed machine in service and the total time in the repair facility are shown to be of phase type. Several performance measures are evaluated. An optimization problem to determine the number of machines to be assigned to the server that will maximize the expected total profit per unit time is discussed. An illustrative numerical example is presented. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 462–480, 2003     

Two‐stage component test plans for testing the reliability of a series system

A system reliability is often evaluated by individual tests of components that constitute the system. These component test plans have advantages over complete system based tests in terms of time and cost. In this paper, we consider the series system with n components, where the lifetime of the i‐th component follows exponential distribution with parameter λ_i. Assuming test costs for the components are different, we develop an efficient algorithm to design a two‐stage component test plan that satisfies the usual probability requirements on the system reliability and in addition minimizes the maximum expected cost. For the case of prior information in the form of upper bounds on λ_i's, we use the genetic algorithm to solve the associated optimization problems which are otherwise difficult to solve using mathematical programming techniques. The two‐stage component test plans are cost effective compared to single‐stage plans developed by Rajgopal and Mazumdar. We demonstrate through several numerical examples that our approach has the potential to reduce the overall testing costs significantly. © 2002 John Wiley & Sons, Inc. Naval Research Logistics, 49: 95–116, 2002; DOI 10.1002/nav.1051     

基于多Agent的编队导弹攻击火力分配的优化研究

目前解决火力分配优化问题的更多的是运用静态的数学模型,忽略了作战是一个激烈对抗的过程.为了更全面地研究编队导弹攻击分配的优化问题,提出了一种基于多Agent的编队导弹攻击火力分配仿真优化研究的方法.首先建立了舰艇Agent的模型,研究了Agent的演化模型,建立了基于Agent的火力分配的优化模型.通过Agent自身的演化,从而达到整个编队导弹攻击的火力分配决策的优化目的.最后给出了仿真试验,对仿真结果数据的分析,验证了方法的可行性.     

舰载直升机兵力使用方案优化建模与仿真

依据舰载直升机兵力使用计划活动的思维机制,分析了计划活动中所涉及的各种主要因素,采用定量与定性分析相结合的方法,建立了兵力使用方案优化的益损值模型,并以舰载直升机反潜作战样式为例,采用软件编程方式实现了该模型,实例表明该方法可为决策者做出科学、有效的决策提供支持。     

改进粒子群算法在导弹火力分配中的应用

粒子群优化算法是一种新兴的优化技术,思想来源于人工生命和演化计算理论.由于该算法简单易实现,可调参数少,目前已得到广泛研究和应用.在建立导弹武器火力分配数学模型的基础上,运用改进粒子群算法对模型进行了最优化求解,实例的计算结果表明该优化算法对于模型的求解具有较好的收敛性.     

多核数字信号处理卷积算法并行优化

针对国防科技大学自主研发的异构多核数字信号处理(digital signal processing, DSP)芯片的特征以及卷积算法自身特点,提出了一种面向多核DSP架构的高性能多核并行卷积实现方案。针对1×1卷积提出了特征图级多核并行方案;针对卷积核大于1的卷积提出了窗口级多核并行优化设计,同时提出了逐元素向量化计算的核内并行优化实现。实验结果表明,所提并行优化方法实现单核计算效率最高能达到64.95%,在带宽受限情况下,多核并行扩展效率可达到48.36%～88.52%,在典型网络ResNet50上的执行性能与E5-2640 CPU相比,获得了5.39倍性能加速。     

基于改进整型遗传算法的稀疏矩形平面阵列优化

为了降低固定稀疏率、固定孔径的稀疏矩形阵列的峰值旁瓣电平,提出一种改进整型遗传算法。该算法在整型遗传算法的基础上,提出了等间隔采样的交叉策略、多点变异策略以及优良基因重组的策略。采取等间隔采样的基因交叉方式,可以有效发挥整型编码的优势,从而提高算法的运行效率;为了提高种群的多样性,防止算法陷入局部最优,采用了多点变异策略;采用优良基因重组技术,加快了算法的收敛速度。仿真结果表明,相比传统的二进制和实数编码,整型编码更为直接高效;与用于稀疏矩形阵列优化的相关算法相比,本文所提算法获得了更优的旁瓣电平,证实了算法的有效性和优越性。     

地基雷达探测临近空间高超声速目标优化部署方法

为提高地基雷达对临近空间高超声速目标的探测能力,探讨了一种实用高效的地基雷达优化部署方法,对地基雷达探测临近空间高超声速目标的难点和数学模型进行了分析,提出了地基雷达探测临近空间高超声速目标的部署原则和量化指标,建立了地基雷达优化部署模型,并进行了信息素引导性控制的蚁群算法设计。仿真结果表明,该方法可实现多种程式地基雷达的优化部署,提高了地基雷达优化部署效率和可操作性,为地基雷达探测临近空间高超声速目标的优化部署提供了一种新思路。     

Pricing and inventory management during new product introduction when shortage creates hype

In this study, we analyze the joint pricing and inventory management during new product introduction when product shortage creates additional demand due to hype. We develop a two‐period model in which a firm launches its product at the beginning of the first period, before it observes sales in the two periods. The product is successful with an exogenous probability, or unsuccessful with the complementary probability. The hype in the second period is observed only when the product is successful. The firm learns the actual status of the product only after observing the first‐period demand. The firm must decide the stocking level and price of the product jointly at the beginning of each of the two periods. In this article, we derive some structural properties of the optimal prices and inventory levels, and show that (i) firms do not always exploit hype, (ii) firms do not always increase the price of a successful product in the second period, (iii) firms may price out an unsuccessful product in the first period if the success probability is above a threshold, and (iv) such a threshold probability is decreasing in the first‐period market potential of the successful product. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 304–320, 2015