铁道车辆轮重测定仪检定装置的研制

为满足铁路货场铁路车辆轮重测定仪的现场检测与维修工作,研制了体积小、重量轻、结构简单的LJ-B型铁路车辆轮重测定仪检定装置。从研制目标、系统结构与原理、研制方案和技术难点及实际运用情况等方面,详细介绍LJ-B型铁路车辆轮重测定仪检定装置。     

基于深度优先搜索的铁路站场遍历算法研究

在列车运行控制系统中,及时准确地了解列车所在位置是非常重要的。卫星定位技术GNSS(GlobalNavigation Satellite System)已经逐渐应用到列车定位技术中,在对列车进行定位时需要对定位数据的可靠性进行验证。车站的定位数据可靠性验证工作建立在对车站站场进行多次遍历获得定位数据的基础上。利用计算机仿真技术模拟列车在站场内遍历能够对现场很难实现的遍历情况进行重复测试。本文对铁路站场与有向图的相似性进行研究,建立基于铁路站场结构的拓扑模型,在此基础上结合站场实际遍历的情况与图的深度优先遍历算法思路,提出一种基于链表数据结构的连续遍历站场的算法。结合实际站场图进行遍历算法仿真,较好地实现了连续遍历并获取较高的遍历效率。     

��½��װ�����վ��ѡַ �Ż�ģ�ͼ��㷨�о�

内陆集装箱空箱站场是集装箱运输公司的内陆空箱调运网络的节点，其布局合理与否对集装箱运输公司降低成本、提高服务质量有重大影响．本文通过对传统的站场选址方法进行研究，根据内陆空箱站场选址的具体特征，建立了内陆集装箱空箱站场选址的混合整数规划模型，并对传统的求解该问题的禁忌搜索算法进行了改进．通过试验表明该改进算法具有较好的全局寻优能力，为集装箱空箱站场选址优化提供了一种新的思路和方法．     

进路搜索数据结构与算法研究

在深入研究站场信号平面图的基础上,对站场信号平面图建立有向无环图的模型,阐述一种在有向无环图中动态生成二叉树的进路搜索算法。验证算法的有效性和实用性。     

JD多车型配送车辆调度问题的模型及其禁忌搜索算法研究

在建立多车型配送车辆调度问题的数学模型的基础上,通过设计一种新的解的表示方法建立了求解该问题的禁忌搜索算法.实验计算证明,该算法不仅可以取得很好的计算结果,而且计算效率较高,收敛速度较快,计算结果也较稳定.     

METADATA EXPANDED SEMANTICALLY BASED RESOURCE SEARCH IN EDUCATION GRID

With the rapid increase of educational resources, how to search for necessary educational resource quickly is one of most important issues. Educational resources have the characters of distribution and heterogeneity, which are the same as the characters of Grid resources. Therefore, the technology of Grid resources search was adopted to implement the educational resources search. Motivated by the insufficiency of currently resources search methods based on metadata, a method of extracting semantic relations between words constituting metadata is proposed. We mainly focus on acquiring synonymy, hyponymy, hypernymy and parataxis relations. In our schema, we extract texts related to metadata that will be expanded from text spatial through text extraction templates. Next, metadata will be obtained through metadata extraction templates. Finally, we compute semantic similarity to eliminate false relations and construct a semantic expansion knowledge base. The proposed method in this paper has been applied on the education grid.     

Floating Car Data Based Nonparametric Regression Model for Short-Term Travel Speed Prediction

A K-nearest neighbor (K-NN) based nonparametric regression model was proposed to predict travel speed for Beijing expressway. By using the historical traffic data collected from the detectors in Beijing expressways, a specically designed database was developed via the processes including data filtering, wavelet analysis and clustering. The relativity based weighted Euclidean distance was used as the distance metric to identify the K groups of nearest data series. Then, a K-NN nonparametric regression model was built to predict the average travel speeds up to 6 min into the future. Several randomly selected travel speed data series, collected from the floating car data (FCD) system, were used to validate the model. The results indicate that using the FCD, the model can predict average travel speeds with an accuracy of above 90%, and hence is feasible and effective.     

Local Search Algorithm with Hybrid Neighborhood and Its Application to Job Shop Scheduling Problem

A new local search method with hybrid neighborhood for Job shop scheduling problem is developed. The proposed hybrid neighborhood is not only efficient in local search, but also can help overcome entrapments while search procedure get trapped at local optima and carry the search to areas of the feasible set with better prospect. New strategies used for breaking out of entrapments are presented and they are helpful for the procedure to improve local optima. A performance comparison of the proposed method with some best-performing algorithms on all 10-job, 10-machine benchmark problems and the other two problems generated by Fisher and Thompson ( ie. , FT6 and FT20) is made. The experiment results show the better optimal performance of the proposed algorithm.     

Network Decomposition and Maximum Independent Set Part Ⅱ：Application Research

According to the researches on theoretic basis in part I of the paper，the spanning tree algorithms solving the maximum independent set both in even network and in odd network have been developed in this part，part Ⅱ of the paper．The algorithms trans form first the general network into the pair sets network，and then decompose the pair sets network into a series of pair subsets by use of the characteristic of maximum flow passing through the pair sets network．As for the even network，the algorithm requires only one time of trans formation and decomposition，the maximum independent set can be gained without any iteration processes，and the time complexity of the algorithm is within the bound of O(｜V｜^3)．However，as for the odd network，the algorithm consists of two stages．In the first stage，the general odd network is transformed and decomposed into the pseudo-negative envelope graphs and generalized reverse pseudo-negative envelope graphs alternately distributed at first；then the algorithm turns to the second stage，searching for the negative envelope graphs within the pseudo-negative envelope graphs only．Each time as a negative envelope graphhas been found．renew the pair sets network by iteration at once．and then tum back to the first stage．So both stages form a circulation process up to the optimum．Two available methods，the adjusting search and the picking-off search are specially developed to deal with the problems resulted from the odd network．Both of them link up with each other harmoniously and are embedded together in the algorithm．Analysis and study indicate that the time complexity of this algorithm is within the bound of O(｜V｜^5)．     

一种求解Job-Shop调度问题的快速禁忌搜索算法

介绍了一种解决Job-Shop调度最短完工时间的有效的快速禁忌搜索算法,该算法首先利用插入算法构造尽可能好的初始解,然后使用禁忌搜索算法改进当前解,用基准实例进行仿真,实验结果表明该算法是可行的和有效的.