A distributed VNS algorithm for optimizing dial-a-ride problems in large-scale scenarios

These days, transportation and logistic problems in large cities are demanding smarter transportation services that provide flexibility and adaptability. A possible solution to this arising problem is to compute the best routes for each new scenario. In this problem, known in the literature as the dial-a-ride problem, a number of passengers are transported between pickup and delivery locations trying to minimize the routing costs while respecting a set of prespecified constraints. This problem has been solved in the literature with several approaches from small to medium sized problems. However, few efforts have dealt with large scale problems very common in massive scenarios (big cities or highly-populated regions). In this study, a new distributed algorithm based on the partition of the requests space and the combination of the routes is presented and tested on a set of 24 different scenarios of a large-scale problem (up to 16,000 requests or 32,000 locations) in the city of San Francisco. The results show that, not only the distributed algorithm is able to solve large problem instances that the corresponding sequential algorithm is unable to solve in a reasonable time, but also to have an average improvement of 9% in the smaller problems. The results have been validated by means of statistical procedures proving that the distributed algorithm can be an effective way to solve high dimensional dial-a-ride problems.     

Forecasting journey time distribution with consideration to abnormal traffic conditions

Travel time is an important index for managers to evaluate the performance of transportation systems and an intuitive measure for travelers to choose routes and departure times. An important part of the literature focuses on predicting instantaneous travel time under recurrent traffic conditions to disseminate traffic information. However, accurate travel time prediction is important for assessing the effects of abnormal traffic conditions and helping travelers make reliable travel decisions under such conditions. This study proposes an online travel time prediction model with emphasis on capturing the effects of anomalies. The model divides a path into short links. A Functional Principal Component Analysis (FPCA) framework is adopted to forecast link travel times based on historical data and real-time measurements. Furthermore, a probabilistic nested delay operator is used to calculate path travel time distributions. To ensure that the algorithm is fast enough for online applications, parallel computation architecture is introduced to overcome the computational burden of the FPCA. Finally, a rolling horizon structure is applied to online travel time prediction. Empirical results for Guangzhou Airport Expressway indicate that the proposed method can capture an abrupt change in traffic state and provide a promising and reliable travel time prediction at both the link and path levels. In the case where the original FPCA is modified for parallelization, accuracy and computational effort are evaluated and compared with those of the sequential algorithm. The proposed algorithm is found to require only a piece rather than a large set of traffic incident records.     

基于聚类网格文件的数据库操作并行联结算法

对数据库运算有很多并行算法。由于联结运算开销大而且使用频繁,所以,联结运算的优化至关重要。作者提出了基于网格文件的两个新的并行算法,分别用于一致关系和下一致关系。因为这里给出的算法避免了当前常用的散列算法中必然的开销很大的划分阶段,所以能够提高联结运算的效率。     

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。     

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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.     

高速公路陡坡弯道路段安全性评价

结合运行车速理论,分析判定陡坡弯道的汽车行驶安全性,并在设计、管理等方面对存在安全隐患路段提出改进措施。