针对自适应巡航的驾驶人风格辨识

车辆进入自适应巡航工况下行驶时,不同风格的驾驶人会对自适应巡航控制系统(Adaptive Cruise Control,ACC)有不同的需求。文章首先通过对不同驾驶人在9种跟随试验下获取的实验数据分析,选取表征驾驶人风格的驾驶特征参数;其次对所有驾驶人驾驶特征参数利用K-mean算法聚类分析,将驾驶人三类,并利用BP神经网络建立辨识模型对驾驶人风格进行辨识。结果表明;文章提出的方法可以较高的准确率对驾驶人风格进行分类,提高自适应巡航系统适应驾驶人的能力。     

基于Intergraph Smart 3D的邮轮电缆自动敷设功能优化开发

Intergraph Smart 3D软件的电缆敷设功能在化工电力行业应用较为广泛,考虑到邮轮电气生产设计中的电缆具有长度长(3 000 km～5 000 km)、种类多、通道网络复杂和分段敷设的特点,直接应用Smart 3D原生的电缆敷设功能进行电缆敷设存在较大的风险。从邮轮电缆敷设需求出发,对Smart 3D原生电缆敷设解决方案进行优化,充分考虑电气设计人员的使用习惯,基于贪心算法和单源最短路径算法(Dijkstra算法)优化算法解决断续托架的电缆敷设和电缆分区敷设最优路径选取的问题,提高电气设计人员的电缆敷设效率。     

Benefit of speed reduction for ships in different weather conditions

Currently, the shipping industry is facing a great challenge of reducing emissions. Reducing ship speeds will reduce the emissions in the immediate future with no additional infrastructure. However, a detailed investigation is required to verify the claim that a 10% speed reduction would lead to 19% fuel savings (Faber et al., 2012).This paper investigates fuel savings due to speed reduction using detailed modeling of ship performance. Three container ships, two bulk carriers, and one tanker, representative of the shipping fleet, have been designed. Voyages have been simulated by modeling calm water resistance, wave resistance, propulsion efficiency, and engine limits. Six ships have been simulated in various weather conditions at different speeds. Potential fuel savings have been estimated for a range of speed reductions in realistic weather.It is concluded that the common assumption of cubic speed-power relation can cause a significant error in the estimation of bunker consumption. Simulations in different seasons have revealed that fuel savings due to speed reduction are highly weather dependent. Therefore, a simple way to include the effect of weather in shipping transport models has been proposed.Speed reduction can lead to an increase in the number of ships to fulfill the transport demand. Therefore, the emission reduction potential of speed reduction strategy, after accounting for the additional ships, has been studied. Surprisingly, when the speed is reduced by 30%, fuel savings vary from 2% to 45% depending on ship type, size and weather conditions. Fuel savings further reduce when the auxiliary engines are considered.     

基于Adaptive Lasso与RF的航班运行风险预测改进研究

为了解决航班运行风险高维数组运算过于复杂的问题,同时为防止模型过度拟合影响预测精度,基于中国民航局发布的风险评估体系,以某航450组真实航班数据为标准样本,首先使用自适应套索算法（Adaptive Lasso）进行降维,从63项风险自变量中筛选出15项独立变量;然后,使用随机森林算法(Random Forest,RF)进行防过拟合处理,结果显示当使用重要度排序前12项变量拟合时,结果误差达到最小值,即得到最终预测指标;最后,构建Adaptive Lasso和RF的二阶段混合模型,同时选取主成分分析(Principal Component Analysis,PCA)、径向基函数(Radial Basis Function,RBF)网络、支持向量机(Support Vector Machine,SVM)3种对比方法,使用十折交叉验证精度.结果表明：Adaptive Lasso方法在筛选掉48项指标后,结果精度未见下降;经RF处理后4种方法评估精度均大于未处理前;Adaptive Lasso-RF混合模型的预测准确率和稳定性均优于PCA、RBF神经网络和SVM等方法.综上说明混合模型实现了有效降维和防过拟合,可大幅提升预测精度,用于解决航班风险预测问题可行并有效.     

基于OpenStreetMap的城市自行车网建模与多判据路径规划

自行车交通是一种健康、绿色、环保的交通出行方式,合理地规划自行车出行路线对于满足骑行者多元化出行需求、构建安全规范的城市交通出行环境具有重要的意义.在对真实骑行者路径选择行为深入分析的基础上,提出了基于Open Street Map的城市自行车网络的构建方法及基于其上的多判据自行车路径优化的数学模型,并给出了求解该模型的一种基于聚类的最优多判据路径规划方法.实验仿真结果表明,该模型及方法能够生成满足骑行者真实需求的多判据路线方案.     

无线传感器网络安全路由协议SNEP的分析与仿真实现

以提供可靠保密通信为目标的安全路由协议的分析是无线传感器网络安全基本研究领域之一．阐述了针对无线传感器网络的攻击手段所采取的措施,研究了安全路由协议,重点研究了其中的传感网络加密协议（Sensor Network Encryption Protocol,SNEP）,并进行了仿真实现,最后针对无线传感网络的攻击方式对SNEP的安全性进行了分析．结果证明SNEP协议具有数据机密性、数据认证、防御重放攻击等安全服务．     

基于DR-System的存贮路径问题研究

本文研究的是基于DR-System的存贮路径问题,即综合考虑配送中心订货成本、配送成本、配送中心和客户库存持有成本的最小化问题．本文提出井运用启发式算法来求解谊问题．首先把问题分解为两个子问题,即配送中心的订货问题和客户的配送问题,分别求解得到问题的初始解;然后,通过分析客户配送提前对总成本的影响,来改进初始解,从而得到谊问题的一个满意解．     

分送式货物配送的优化

在分析分配式货物配送现状基础上,对物流中心的配送问题从配装和运输两个环节进行优化。建模时主要考虑货车的类型、体积、载重等约束条件,以车辆的配送路径最短、拼装货品最多为优化目标,研究配送的优化模型和算法。     

Improving maritime inventory routing: application to a Brazilian petroleum case

The crude oil offloading and supply problem (COSP) is a type of operation maritime inventory routing (MIR) problem encountered by petroleum companies. In COSP, the company not only is responsible for the ship scheduling to carry the crude oil from production sites to discharge ports but also must maintain inventory levels at both ports (production and consumption) between safety operational bounds to avoid disruptions in its crude oil production and/or refining processes. We show how to improve significantly the decision-making process in a Brazilian petroleum company using a mixed-integer linear programming (MILP) model to represent COSP. Comparison tests with a current ship-scheduling method adopted in the company indicated that the use of the MILP model increased the transportation efficiency and reduced costs by 20% on average. In addition to the quantitative gains, the use of a MILP model to solve COSP has succeeded when encountering real-life events, such as variation in production or consumption rates, berth unavailability, and changes in the storage capacities at ports.     

Order-first split-second methods for vehicle routing problems: A review

Cluster-first route-second methods like the sweep heuristic (Gillett and Miller, 1974) are well known in vehicle routing. They determine clusters of customers compatible with vehicle capacity and solve a traveling salesman problem for each cluster. The opposite approach, called route-first cluster-second, builds a giant tour covering all customers and splits it into feasible trips. Cited as a curiosity for a long time but lacking numerical evaluation, this technique has nevertheless led to successful metaheuristics for various vehicle routing problems in the last decade. As many implementations consider an ordering of customers instead of building a giant tour, we propose in this paper the more general name of ordering-first split-second methods. This article shows how this approach can be declined for different vehicle routing problems and reviews the associated literature, with more than 70 references.