Optimum design of tilting bogie frame in consideration of fatigue strength and weight

This paper addresses the use of finite-element (FE) analysis to calculate the fatigue strength of a bogie frame, for the development of tilting trains in Korea. A multi-body dynamic analysis was performed to extract the load condition by tilting on curves. Using the results of the multi-body dynamic analysis and the load scenario setout in the UIC standard, FE analysis was performed to obtain the stress distribution and to calculate the fatigue strength. An attempt was made to minimize the weight of the bogie frame using a back-propagation artificial neural network (ANN). The results of this study reveal that the stresses at some nodes are near the fatigue limit in the Goodman diagram and by using back-propagation ANN, the weight of the bogie frame could be reduced by 4.7%.     

变步长BP网络优化导航雷达跟踪滤波系统的研究

本文提出了采用变步长ＢＰ网络实时处理导航雷达目标跟踪滤波数据。其原理是在ＢＰ算法中加入变动量因子,用Ｎ层变步长寻优进行前馈神经网络的学习。该算法能够根据输入时间序列的特点自适应调整网络优化步长,对匀速和变加速运动目标的稳定跟踪精度分别在７．５ ｍ 和１１ ｍ 以内,而对急转弯的目标抖动２～４ 次就能及时跟踪上     

Optimization models for differentiating quality of service levels in probabilistic network capacity design problems

This paper develops various chance-constrained models for optimizing the probabilistic network design problem (PNDP), where we differentiate the quality of service (QoS) and measure the related network performance under uncertain demand. The upper level problem of PNDP designs continuous/discrete link capacities shared by multi-commodity flows, and the lower level problem differentiates the corresponding QoS for demand satisfaction, to prioritize customers and/or commodities. We consider PNDP variants that have either fixed flows (formulated at the upper level) or recourse flows (at the lower level) according to different applications. We transform each probabilistic model into a mixed-integer program, and derive polynomial-time algorithms for special cases with single-row chance constraints. The paper formulates benchmark stochastic programming models by either enforcing to meet all demand or penalizing unmet demand via a linear penalty function. We compare different models and approaches by testing randomly generated network instances and an instance built on the Sioux–Falls network. Numerical results demonstrate the computational efficacy of the solution approaches and derive managerial insights.     

Airline network competition: Full-service airlines, low-cost airlines and long-haul markets

The paper discusses airline network competition. Low-cost airlines and conventional airlines have distinctly different strategies and network types. This determines their ability to compete with other airlines in specific markets. The paper discusses the lack of competition between conventional airlines in local markets, and sees why low-cost airlines are the primary source of competition in such markets. Conventional airlines are relatively strong on long-haul markets, using their networks to keep costs per seat relatively low. Charter airlines show that a long-haul low-cost strategy is feasible For scheduled low-cost airlines, this may be more difficult, but this does not automatically mean that low-cost airlines cannot enter thick long-haul markets.     

An easy procedure to determine Magic Formula parameters: a comparative study between the starting value optimization technique and the IMMa optimization algorithm

In 2004, a new searching algorithm for Magic Formula tyre model parameters was presented. Now, a summary of the results, for pure and combined slip, that this algorithm is able to achieve is presented. The Magic Formula tyre model needs a set of parameters to describe the tyre properties. The determination of these parameters is dealt with in this article. A new method, called IMMa Optimization Algorithm (IOA), based on genetic techniques, is used to determine these parameters. Here, we show the computational cost that has been used to obtain the optimum parameters of every characteristic of the Magic Formula tyre model, called Delft Tyre 96. The main advantages of the method are its simplicity of implementation and its fast convergence to optimal solution, with no need of deep knowledge of the searching space. Hence, to start the search, it is not necessary to know a set of starting values of the Magic Formula parameters (null sensitivity to starting values). The search can be started with a randomly generated set of parameters between [0, 1]. Nowadays, MF-Tool, an application developed by TNO, uses an optimization technique to fit Magic Formula parameters from Matlab toolbox [van Oosten, J.J.M. and Bakker, E., 1993, {Determination of magic tyre model parameters}. Vehicle System Dynamics, 21, 19–29; van Oosten, J.J.M., Savi, C., Augustin, M., Bouhet, O., Sommer, J. and Colinot, J.P., 1999, {Time, tire, measurements, forces and moments, a new standard for steady state cornering tyre testing}. EAEC Conference, Barcelona, 30 June–2 July.]. We refer to that algorithm as the starting value optimization technique. The comparison between the optimization technique employed by TNO and the proposed IOA method is discussed in this article. In order to give a relative idea of adjustment accuracy, the sum-squared error and the mean-squared error, from the curves of the tyre model with the parameters optimized by both applications compared with test data are evaluated.     

Application of genetic algorithms for joint optimization of signal setting parameters and dynamic traffic assignment for the real network data

This paper presents the joint optimization of signal setting parameters and dynamic user equilibrium (DUE) traffic assignment for the congested urban road network. The simulation-based approach is employed to obtain the DUE condition for the case of multiple-origin multiple-destination traffic flows. The dynamic traffic assignment simulation program (DTASP), developed in C language is used to assign the traffic dynamically on the road network, whereas method of successive averages (MSA) is modified and used to arrive at the DUE condition. The artificial intelligence technique of genetic algorithms (GAs) is applied to obtain the optimal signal setting parameters and path flow distribution factor for DUE condition. The methodology developed in such a way that joint optimization of signal setting parameters with DUE is obtained. The proposed method is applied to the real network data of Fort Area of Mumbai city comprising of 17 nodes and 56 unidirectional links with 72 Origin–Destination pairs, where all the 17 nodes are signalized intersections. The traffic flow condition for the optimized signal setting parameters is considerably improved compared to the existing signal settings. The results prove that the GA is an effective technique to solve the joint optimization problem for the real network data.     

Ant Colony Routing algorithm for freeway networks

Dynamic traffic routing refers to the process of (re)directing vehicles at junctions in a traffic network according to the evolving traffic conditions. The traffic management center can determine desired routes for drivers in order to optimize the performance of the traffic network by dynamic traffic routing. However, a traffic network may have thousands of links and nodes, resulting in a large-scale and computationally complex non-linear, non-convex optimization problem. To solve this problem, Ant Colony Optimization (ACO) is chosen as the optimization method in this paper because of its powerful optimization heuristic for combinatorial optimization problems. ACO is implemented online to determine the control signal – i.e., the splitting rates at each node. However, using standard ACO for traffic routing is characterized by four main disadvantages: 1. traffic flows for different origins and destinations cannot be distinguished; 2. all ants may converge to one route, causing congestion; 3. constraints cannot be taken into account; and 4. neither can dynamic link costs. These problems are addressed by adopting a novel ACO algorithm with stench pheromone and with colored ants, called Ant Colony Routing (ACR). Using the stench pheromone, the ACR algorithm can distribute the vehicles over the traffic network with less or no traffic congestion, as well as reduce the number of vehicles near some sensitive zones, such as hospitals and schools. With colored ants, the traffic flows for multiple origins and destinations can be represented. The proposed approach is also implemented in a simulation-based case study in the Walcheren area, the Netherlands, illustrating the effectiveness of the approach.     

铁路通信信号标准及基础资料在线查询系统简介

利用现有成熟的信息技术,实现对标准文件的统一集中、规范化、安全化管理,为所属技术、科研人员提供简便有效的标准、规范的获取途径。     

秦沈DC-7程控调度分机优化方案的分析与研究

分析秦沈线当前DC-7程控调度分机存在的问题,借鉴既有线电气化区段使用情况,提出合理优化解决方案。     

大学生网络生态文明的危机与构建

文章在阐述网络生态文明内涵的基础上，探讨了网络生态污染的种种表现及引起大学生文明失范现象，并从建设主流网站、加强污染院监控、培育监管队伍、加强宣传教育等方面提出了修复网络生态引导大学生文明成长的对策。