使用分类和聚类提高搜索引擎的可用性

由于很多Web用户面对搜索引擎搜索出来的成千上万条结果记录没有耐心一页一页地翻找,搜索出来的内容就不能得到有效的利用.自动分类聚类技术将是搜索引擎进一步改善搜索效率的一个很重要的方面.介绍联合使用分类聚类技术来改善搜索结果的表示形式,提高搜索引擎的可用性.     

结构模糊可靠性分析

结构破坏准则实际上是带有模糊性的，要合理判断结构强度必须依靠模糊概率方法。本文采用基于模糊判决的限界搜索法，给出了计算结构模糊可靠性清晰解的方法。以受集中力的两端刚固梁和船首底板砰击强度为例进行了数值计算，并讨论了容差变化对模糊可靠度指标的影响。     

基于时间序列相似性搜索的交通流短时预测方法

为了进一步提高交通流短时预测的效果,在分析现有预测模型存在问题的基础上,设计了1种基于时间序列相似性搜索的交通流短时多步预测方法.利用界标模型对交通流时间序列数据进行模式表示,在历史数据库中搜索与当前交通流时间序列相似度较高的历史时间序列,进而确定与预测时刻相对应的历史数据,利用回声状态网络模型实现交通流的短时多步预测.采用某特大城市快速路5 min采样间隔的交通流量数据进行实验验证和对比分析.实验结果表明,回声状态网络模型的预测精度分别比ARIMA模型和BP神经网络模型提高了6.25%和3.85%,以时间序列相似性搜索结果作为模型输入数据能够进一步提高交通流短时预测的精度.      

通用快速简易气门调整法

在详细的理论分析基础上，提出了一种快速简易的气门调整方法，即不论往复式四行程内燃机的曲轴处于任何位置，调整处于可调位置的进气门和排气门，然后转动曲轴一圈，调整原先处于不可调位置的进气门和排气门。用此种方法可调整任意类型和缸数的四冲程内燃机的气门间隙。     

航班快速恢复建模与仿真研究

随着民用航空的发展与竞争,航班延误不仅影响航空飞行的安全与正常,更与航空公司的运营效率、运营成本及乘客利益息息相关。针对某一恶劣天气影响,对某公司受影响航班进行重新调配,考虑到航班的备降、盘旋等待、延误、取消等多种状态,以总成本最小为目标函数,建立航班快速恢复模型,通过MATLAB运用遗传算法设计航班恢复算法进行求解,得出最经济的航班恢复方案。     

Free-floating bike sharing: Solving real-life large-scale static rebalancing problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible.Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs.Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time.     

The load-dependent vehicle routing problem and its pick-up and delivery extension

The present paper examines a Vehicle Routing Problem (VRP) of major practical importance which is referred to as the Load-Dependent VRP (LDVRP). LDVRP is applicable for transportation activities where the weight of the transported cargo accounts for a significant part of the vehicle gross weight. Contrary to the basic VRP which calls for the minimization of the distance travelled, the LDVRP objective is aimed at minimizing the total product of the distance travelled and the gross weight carried along this distance. Thus, it is capable of producing sensible routing plans which take into account the variation of the cargo weight along the vehicle trips. The LDVRP objective is closely related to the total energy requirements of the vehicle fleet, making it a credible alternative when the environmental aspects of transportation activities are examined and optimized. A novel LDVRP extension which considers simultaneous pick-up and delivery service is introduced, formulated and solved for the first time. To deal with large-scale instances of the examined problems, we propose a local-search algorithm. Towards an efficient implementation, the local-search algorithm employs a computational scheme which calculates the complex weighted-distance objective changes in constant time. Solution results are presented for both problems on a variety of well-known test cases demonstrating the effectiveness of the proposed solution approach. The structure of the obtained LDVRP and VRP solutions is compared in pursuit of interesting conclusions on the relative suitability of the two routing models, when the decision maker must deal with the weighted distance objective. In addition, results of a branch-and-cut procedure for small-scale instances of the LDVRP with simultaneous pick-ups and deliveries are reported. Finally, extensive computational experiments have been performed to explore the managerial implications of three key problem characteristics, namely the deviation of customer demands, the cargo to tare weight ratio, as well as the size of the available vehicle fleet.     

一种可伸缩的预测性快速运动向量搜索算法

基于钻石搜索的特点，提出了搜索距的概念．通过对不同搜索距的检测点特性的研究，并吸收了PMVFAST算法中“见好就收”的思想和初始预测候选运动向量集的概念，提出了一种新的可伸缩的预测性十字方块快速运动搜索算法，该算法以检测点的块失真特性统计为基础，制定出精确可控的可适应搜索准则．大量模型实验表明：该算法能获得更好的视频质量，同时，拥有良好的搜索速度伸缩性，在允许图象质量有0．05dB降低时，搜索速度能提高1．5-2．5倍．     

一种基于极坐标的快速邻域搜索算法

一般邻域搜索方法面临着邻域定义的难点：定义的邻域较小，搜索就可能很快陷入局部最优，相反，则搜索效率会显著下降．针对这一问题，提出了一种基于极坐标的快速邻域搜索算法．试验证明，该算法能有效地解决邻域定义问题，并能在一定程度上解决常用的优化方法还较难解决的非凸集问题，对于一般复杂度问题，有较小的时间和空间复杂度。     

固定容量设备选址问题的求解算法研究

由于大多数选址问题都已证明是NP-难问题,研究问题的近似算法成为其关键技术。本文就是基于大规模邻域搜索(VLSN)技术的迭代局域搜索(ILS)算法来解决资源固定容量设备选址问题(CFLP)。为了说明VLSN技术的有效性,本文又实现了多点下降算法,并且结合大规模算法和多点下降算法求得了质量更好的解。