基于模拟退火算法的动态联盟盟员的动态选择

为了顺应21世纪知识经济时代竞争的需要,在制造业出现了动态联盟的先进制造模式,从而使得对动态联盟的研究成为当前学术界热点问题之一。目前,国内外在研究动态联盟盟员选择主要集中于组盟时的盟员选择,是一种静态选择,与动态联盟“快捷变化”的特性不符。由于知识的形性、外溢性、无地域性、成员间的合作竞争性等,使得动态联盟不可避免会产生知识资产冲突,从而导致着盟员的动态更迭。为此,基于模拟退火算法的思想,本文设计了一种解决动态联盟中盟员动态选择的算法,该算法很好地解决了动态联盟中盟员如何被动态选择和淘汰的问题,实例也表明该算法是符合实际运做的。当然,本算法也存在着一些有待继续研究的问题。     

Analyzing multivariate longitudinal binary data: A generalized estimating equations approach

The authors consider regression analysis for binary data collected repeatedly over time on members of numerous small clusters of individuals sharing a common random effect that induces dependence among them. They propose a mixed model that can accommodate both these structural and longitudinal dependencies. They estimate the parameters of the model consistently and efficiently using generalized estimating equations. They show through simulations that their approach yields significant gains in mean squared error when estimating the random effects variance and the longitudinal correlations, while providing estimates of the fixed effects that are just as precise as under a generalized penalized quasi‐likelihood approach. Their method is illustrated using smoking prevention data.     

图书馆清产核资以后的思考

通过清产核资,暴露出对馆藏文献资源的管理、开发与利用存在着不足.在分析原因的基础上,提出几点建议.     

Dynamic Pricing in e‐Services under Demand Uncertainty

High volatility of the e‐services market, due to increasing competition, low life cycle of products, and easy availability of information about competing service offerings to customers, makes the demand for service offerings quite uncertain. Revenue management in such markets calls for real‐time techniques to learn the demand and its dependence on both the price and the service level associated with the service offering. We assume firms reply on exploratory approaches for demand estimation, in which firms experiment with different service offerings in order to simultaneously learn the demand while doing business. Such exploration and learning process can be costly without supervision. As reported by Rothschild (Journal of Economic Theory, 9 185‐202, 1974), traditional Bayesian dynamic control approaches may conclude with suboptimal offerings. We propose a novel demand learning approach that is guaranteed to converge to the optimal offering. The approach combines simulated annealing algorithm with Bayesian learning. We further present intelligent techniques that adaptively reduce the effort of exploration on suboptimal service offerings so as to improve the long‐run average profit.     

模拟核算在航空集团公司运用初探

模拟核算作为一种行之有效的管理模式在西南航空公司进行了成功试点 ;试点结果表明 ,模拟核算中的建立责任中心、制定模拟价格、编制模拟预算等一系列基本做法在航空集团公司中具有进一步推广应用的价值。     

三维限制TSP的退火模拟算法

给出了一种具有全局优化特性的三维限制TSP的求解方法,研究了针对三维限制TSP的退火模拟模型的建立、扰动的形成和算法参数的选取,最后给出了实验例子。     

SIMULATED MAXIMUM LIKELIHOOD APPLIED TO NON-GAUSSIAN AND NONLINEAR MIXED EFFECTS AND STATE–SPACE MODELS

The paper presents an overview of maximum likelihood estimation using simulated likelihood, including the use of antithetic variables and evaluation of the simulation error of the resulting estimates. It gives a general purpose implementation of simulated maximum likelihood and uses it to re‐visit four models that have previously appeared in the published literature: a state–space model for count data; a nested random effects model for binomial data; a nonlinear growth model with crossed random effects; and a crossed random effects model for binary salamander‐mating data. In the case of the last three examples, this appears to be the first time that maximum likelihood fits of these models have been presented.     

一种改进的模拟退火图像盲复原算法

通过分析均匀分布与Cauchy分布的分布机制,提出了一种改进的模拟退火图像盲复原算法,该算法选择Cauchy分布为随机扰动量来产生状态扰动函数。通过计算机仿真,验证了该算法对初值的鲁棒性和复原的效果优于基于均匀分布随机扰动量模拟退火盲解卷积算法,提高了收敛到最优解的速度。     

基于FPGA的模拟信号源系统设计

提出了一种基于现场可编程门阵列(FPGA)的全球定位系统(GPS)卫星信号模拟源系统的设计方案。FPGA作为一种常用的可编程器件,将其应用到模拟信号源系统中,并配合射频模块,实现了多个频点的程序控制,产生出大量具有高稳定度和准确度的不同频率的GPS卫星信号,减少了多个频点的开发周期,降低了风险。     

模拟退火并行粒子群优化算法程序设计与研究

针对粒子群优化算法后期收敛差和模拟退火算法全局优化能力强的特点,建立模拟退火并行粒子群优化算法(SA-PSO算法)模型。利用MATLAB语言开发SA-PSO算法工具箱,实现SA-PSO算法的程序设计,高效、稳定地提高算法全局寻优能力。