分类存储返回型与S型拣选路径随机模型的比较研究

物流配送中心中,减小订单拣选行走距离进而优化人工拣选作业系统可有效提高客户满意度,降低成本.货位指派和拣选方式是影响拣选行走距离的两个重要因素.作者在分类存储的货位指派策略下、分别对返回型和S型拣选方式,建立了拣选距离随机模型.仿真结果表明,模型结果能在误差允许条件下较好地与仿真逼近.通过在4种物品订购频率和货位分配情况下对返回型和S型拣选方式的比较,得出两种拣选方式各自适用的情况.     

提示信息特征对秘书问题决策影响的仿真实验研究

针对具有提示信息的秘书问题,首先分析了提示信息特征变化对决策结果的可能影响.然后在此基础上,提出了在最大值标杆策略下研究提示信息的变化特征对决策结果的影响,接着阐述了仿真试验的理论假设和设计,通过仿真试验考察了提示信息的不同变化对仿真结果的影响;最后给出了对仿真结果的分析和探讨,仿真结果验证了理论假设的判断.     

基于遗传算法的车间作业计划仿真研究

将仿真技术和遗传算法相结合,根据生产车间的资源情况、优化目标等建立了生产调度仿真模型,然后对仿真输出结果进行统计,针对统计结果应用遗传算法对调度决策进行优化.仿真优化结果说明了该集成优化方法是有效性的.     

时变耦合作用下一类离散Winfree模型的同步性分析北大核心CSCD

文章研究了一类耦合强度随时间呈周期性变化的Winfree模型.在适当的假设条件下,证明了振子的最大相位差是随耦合强度系数K的变化周期为时间间隔在不断减小,进而给出了该系统在一定条件下发生相位同步行为的充分条件.最后,给出了两组具体的振子耦合作用方式,并通过数值仿真实验验证了理论结果的正确性.     

道路交通拥堵自动检测的改进加州算法及仿真

本文研究了高速公路交通拥堵自动检测算法.利用改进的加州算法,获得了用VISSIM软件对高速公路车流量情况的仿真数据及结果,仿真结果表明改进加州算法的检测结果良好.     

基于期货、期权与现货组合的采购决策和风险控制研究

针对企业大宗原材料采购容易受到上游价格和下游需求的不确定性影响这一问题,本文以制造商(或分销商)多阶段采购决策为研究对象,建立了包含期货、期权和现货三种采购方式的多阶段组合采购决策模型,以此来应对采购中的价格风险和库存风险.结合某钢构厂原材料采购问题,采用蒙特卡罗仿真方法进行求解.通过对比组合方式与现货方式的求解结果,证明了组合采购方式能够在各种采购环境下为采购商带来更高更稳定的利润,所提出的组合采购决策模型能够有效的规避风险.     

模块式建模法及其数值解法在液压仿真中的应用

本文论述了液压大系统仿真的模块式建模法及其相应的隐式状态方程数值解法——代数-积分混合算法.根据模块式建模法建立了液压调速系统的数学模型,并利用代数-积分混合算法对调速系统进行了数值仿真,仿真结果与实验结果十分吻合.该建模法及其算法首次在液压大系统仿真中得到应用.     

基于多种用海功能的海域使用权拍卖机制研究

海域使用权拍卖是对海域资源进行市场化配置的重要方式.基于海域资源的立体性和层次性特征,提出了多种用海功能约束下的海域使用权拍卖机制,设计了综合效用函数,对海域使用权进行经济价值与生态补偿的综合评价,促进海域资源的多层次利用与开发.仿真结果表明:相比较于单一功能的海域使用权拍卖,多属性拍卖能够改善海域使用权拍卖效率,同时拍卖结果也提高了政府对海域使用权拍卖的满意度和最终效用,为我国海域使用权拍卖方式的创新提供了理论基础.     

内生网络环境下2-步邻域内的局部策略互动及其仿真

考察内生网络环境下局中人与2-步邻域内的邻居进行的局部协同对策,较为完整地给出了均衡网络的结构特性,以及费用参数和互动半径对于均衡结构的影响. 基于 NetLogo仿真系统,编制了局部互动仿真模拟实验程序. 仿真结果显示,网络生成的动态进程对于网络均衡结果存在很大影响. 结果对于解决社会和经济领域中的互动问题可提供策略性指导.     

爆炸冲击载荷下航空铝合金平板动态响应数值分析方法

为得到适用于爆炸冲击载荷下航空铝合金平板动态响应的数值分析方法,采用LS-DYNA显式动力学分析软件对爆炸冲击载荷下的铝合金平板进行数值仿真计算.主要研究了不同的任意Lagrange-Euler(拉格朗日-欧拉)网格（ALE）输运步算法、流固耦合方式、流固耦合点数量、网格尺寸、有限元单元类型对计算结果的影响.通过计算结果与实验结果的分析对比,表明采用van Leer+HIS输运步算法、罚函数耦合方式、在流体网格与结构网格之间采用3个耦合点、结构网格尺寸与空气域网格尺寸比例设为2∶1、结构单元采用163号壳单元时可以较为准确地计算航空铝合金平板在爆炸冲击载荷下的动态响应,并且能提高计算效率,节约计算时间.     

基于L-M方法的液压油源系统的可靠性分析

本文结合液压伺服系统的工程实际,运用了L-M方法,对恒压油源系统进行可靠性分析与建模,并给出了系统可靠度的定量评估结果,最后利用该模型对试验模拟数据进行分析,这对工程设计具有重要的指导作用。     

两相同部件并联部分可修复系统的可靠性分析

用C_0半群理论,研究了一类两相同部件并联部分可修复系统解的存在惟一性及指数稳定性,并从本征向量的角度讨论了此系统的一些主要可靠性指标,给出了瞬态可用度的数值模拟.     

Testing schedule performance and reliability for train stations

On busy congested rail networks, randomdelays of trains are prevalent, and these delays have knock-on effects which result in a significant or substantial proportion of scheduled services being delayed or rescheduled. Here we develop and experiment with a simulation model to predict the probability distributions of these knock-on delays at stations, when faced with typical patterns of on-the-day exogenous delays. These methods can be used to test and compare the reliability of proposed schedules, or schedule changes, before adopting them. They can also be used to explore how schedule reliability may be affected by proposed changes in operating policies, for example, changes in minimum headways or dwell times, or changes in the infrastructure such as, layout of lines, platforms or signals. This model generates a reliability analysis for each train type, line and platform. We can also use the model to explore some policy issues, and to show how punctuality and reliability are affected by changes in the distributions of exogenous delays.     

Weibull 分布等分位数数据填充算法及其应用

基于作者曾提出的处理非随机删失数据的迭代算法,针对weibull分布相同定时截尾型试验数据,通过改变数据的填补方式,在保证由算法所得的参数估计的相合性和不变性的前提下,使得改进后的算法所得的虚拟完全数据更接近于真实的完全数据.模拟研究表明,对于删失数据情形下可靠度的区间估计问题,改进后的算法更加精确.     

Reliability assessment for load‐sharing systems with exponential components using statistical expansion as a correction

Among recent system models, one specific type of system is generally used to model the dependence among components. Components are connected parallel in such systems as they fail one by one and are supposed to share the system work load. The model is thus referred to as the load‐sharing system model. Despite the availability of extensive reliability assessment methods for different systems, load‐sharing systems have not received enough attention from the scholars who have studied reliability assessment so far. Load‐sharing systems are generally designed for high levels of reliability. Therefore, tests for such systems can be expensive and time consuming. Limitation on resources always leads to small test sample sizes. This increases the difficulties associated with obtaining an accurate and robust system reliability assessment result. This paper proposes a novel assessment method for a certain type of load‐sharing system with components following exponential lifetime distributions. Based on the parameter estimation of the system reliability model, we introduce the Winterbottom‐Cornish‐Fisher asymptotic expansion method for implementing a correction of normal approximation. We demonstrate the accuracy of our method through a series of examples and simulation studies.     

一类二元相关威布尔分布的可靠性问题

本文考虑生存函数为${\ol{F}(x_{1},x_{2})}=\exp\{-[(x_{1}^{1/\alpha}/\theta_{1})^{1/\delta}+(x_{2}^{1/\alpha}/\theta_{2})^{1/\delta}]^{\delta}\},\;x_{i}>0,\;\alpha>0$, $1\geq\delta>0,\;\theta_{i}>0\;(i=1,2)$的二元威布尔分布的两种可靠性问题, 提出可靠度$\pr$的估计并讨论了它们的渐近性, 最后还作了模拟计算.     

Modelling redundancy allocation for a fuzzy random parallel-series system

Due to subjective judgment, imprecise human knowledge and perception in capturing statistical data, the real data of lifetimes in many systems are both random and fuzzy in nature. Based on the fuzzy random variables that are used to characterize the lifetimes, this paper studies the redundancy allocation problems to a fuzzy random parallel-series system.Two fuzzy random redundancy allocation models (FR-RAM) are developed through reliability maximization and cost minimization, respectively. Some properties of the FR-RAM are obtained, in which an analytical formula of reliability with convex lifetimes is derived and the sensitivity of the reliability is discussed. To solve the FR-RAMs, we first address the computation of reliability. A random simulation method based on the derived analytical formula is proposed to compute the reliability with convex lifetimes. As for the reliability with nonconvex lifetimes, the technique of fuzzy random simulation together with the discretization method of fuzzy random variable is employed to compute the reliability, and a convergence theorem of the fuzzy random simulation is proved. Subsequently, we integrate the computation approaches of the reliability and genetic algorithm (GA) to search for the approximately optimal redundancy allocation of the models. Finally, some numerical examples are provided to illustrate the feasibility of the solution algorithm and quantify its effectiveness.     

Reliability analysis of an Attitude Determination and Control System (ADCS) through the RAMSAS method

Reliability analysis of modern large-scale systems is a challenging task which could benefit from the jointly exploitation of recent model-based approaches and simulation techniques to flexibly evaluate the system reliability performances and compare different design choices. In this context, RAMSAS, a model-based method which supports the reliability analysis of systems through simulation by combining the benefits of popular OMG modeling languages with wide adopted simulation and analysis environments, has been recently proposed. This paper shows the effectiveness of RAMSAS through a real case study concerning the reliability analysis of an Attitude Determination and Control System (ADCS) of a satellite.     

一种新的恒加试验下双参数指数型产品的可靠性分析

针对双参数指数型产品,在具有二项移走(即在每个观测时刻产品的移走数服从二项分布)的分组寿命试验下,研究了分组时刻的确定方法,推导出门限参数、寿命参数和移走概率的极大似然估计。进而,讨论了双参数指数型产品在具有二项移走的恒加寿命分组试验下的可靠性分析问题。利用加速寿命方程,给出了双参数指数型产品的可靠性估计。最后给出随机模拟例子验证了结论的正确性。     

New maximum entropy-based algorithm for structural design optimization

A new algorithm based on nonlinear transformation is proposed to improve the classical maximum entropy method and solve practical problems of reliability analysis. There are three steps in the new algorithm. Firstly, the performance function of reliability analysis is normalized, dividing by its value when each input is the mean value of the corresponding random variable. Then the nonlinear transformation of such normalized performance function is completed by using a monotonic nonlinear function with an adjustable parameter. Finally, the predictions of probability density function and/or the failure probability in reliability analysis are achieved by looking the result of transformation as a new form of performance function in the classical procedure of maximum entropy method in which the statistic moments are given through the univariate dimension reduction method. In the proposed method, the uncontrollable error of integration on the infinite interval is removed by transforming it into a bounded one. Three typical nonlinear transformation functions are studied and compared in the numerical examples. Comparing with results from Monte Carlo simulation, it is found that a proper choice of the adjustable parameter can lead to a better result of the prediction of failure probability. It is confirmed in the examples that result from the proposed method with the arctangent transformation function is better than the other transformation functions. The error of prediction of failure probability is controllable if the adjustable parameter is chosen in a given interval, but the suggested value of the adjustable parameter can only be given empirically.