灵活编组条件下轨道交通客货协同运输方案优化

基于灵活编组运营组织模式特点，综合考虑客流与货流之间的竞争关系，以列车编组类型及列车发车间隔为主要决策变量，以乘客等待时间和运营公司运营成本极小化为目标，构建灵活编组条件下轨道交通客货协同运输方案混合整数线性规划模型，得到系统优化的列车编组方案、 运行图和客货协同运输方案。当给定编组类型集合且没有货流输入时，本文所构建模型即可退化为传统的固定编组模式下客流运输优化模型。以北京地铁八通线为例设计数值实验，验证了所提模型的有效性，所有实验均由VB语言调用CPLEX优化软件进行求解。算例结果表明，相较于固定编组模式的单一客流运输，本文方法可在乘客平均等待时间仅增加1.1 min的情况下，降低 约41.86%的运营成本，大幅度增加运营收益，更好地实现运输服务质量和运营成本的均衡。     

基于动态规划的轨检车波形数据里程偏差修正研究

轨检车在铁路线路状态检测和养护维修方面发挥着不可替代的作用.历史检测数据具有可比性是获取可靠线路状态变化趋势的关键基础,因而也是开展线路状态修的基础.影响检测数据可比性的主要因素是里程偏差.既有研究基于区段上各采样点里程偏移为常数,利用相关分析修正里程偏差.然而,现场生产实践和轮轨关系研究表明,里程偏移量是一个随机变量.本文研究建立了轨检车数据采样点最优配对模型,捕捉每一个采样点的里程偏移量,建立的模型被用来修正某线路的17次检测数据,修正后的检测数据展示了模型的可靠性和现场应用可行性.     

智能车避障路径规划方法研究

避障路径规划是智能车技术的关键部分,对智能车研究具有重大意义,正确的选择规划方法至关重要。本文首先初步选定人工势场法规划路径,仿真得知传统人工势场法规划出的路径存在局部最优、碰撞及达不到目标点的问题。因此提出改进人工势场法,通过改变势场函数和设定初始条件来解决此问题。最后,为了规划出能够同时避开静态和动态障碍物且能到达目标点的理想路径,在改进人工势场法中加入速度元素,经过仿真,证明了基于速度的改进人工势场法在智能车避障路径规划中的可行性和优越性。     

Assessing the viability of enabling a round-trip carsharing system to accept one-way trips: Application to Logan Airport in Boston

Although one-way carsharing is suitable for more trip purposes than round-trip carsharing, many companies in the world operate only in the round-trip market. In this paper, we develop a method that optimizes the design of a one-way carsharing service between selected origin–destination pairs of an existing round-trip carsharing system. The goal is to supplement the established round-trip services with new one-way services and increase profitability. We develop an integer programming model to select the set of new one-way services and apply it to the case study of Boston, USA, considering only trips with one endpoint at a station in the round-trip Zipcar service network and the other endpoint at Logan Airport. The airport was chosen as a necessary endpoint for a one-way service because it is a very significant trip generator for which the round-trip carsharing is not suitable. Results show that these supplemental one-way services could be profitable. Enabling relocation operations between the existing round-trip stations and the Airport greatly improves the demand effectively satisfied, leads to an acceptable airport station size (in terms of the number of parking spots required), and is profitable; however, these benefits come with the need to manage relocation operations.     

Stochastic optimization approach for the car placement problem in ridesharing systems

With the increasing fuel prices and the pressure towards greener modes of transportation, ridesharing has emerged as an alternative to private car ownership and public transportation. In this paper, we focus on a common destination ridesharing system which is of interest in large organizations such as companies and government offices. Particularly, such organizations are looking at using company owned vehicles to offer a ridesharing service by which employees carpool to work thus leading to several benefits that include decreasing pressure on on-campus parking spaces, lowering localized on-campus congestion, in addition to offering a greener transportation mode while lowering transportation costs for employees. Based on discussions with our industry partners, optimizing the distribution of limited number of company vehicles while insuring robustness against unlikely vehicle unavailability is of critical importance. Thus in this paper, we present a stochastic mixed integer programming model to optimize the allocation of shared vehicles to employees while taking into account the unforeseen event of vehicle unavailability which would require some participants to take own vehicles or rerouting of existing vehicles. Since solving the proposed model to optimality is computationally challenging for problems of large sizes, we also propose a heuristic that is capable of finding good quality solutions in limited computational time. The proposed model and heuristic are tested on several instances of varying sizes showing the computational performance. Finally, a test case based on the city of Rome, Italy is presented and insights related to vehicle distribution and travel time savings are discussed.     

Train scheduling for minimizing passenger waiting time with time-dependent demand and skip-stop patterns: Nonlinear integer programming models with linear constraints

This paper focuses on how to minimize the total passenger waiting time at stations by computing and adjusting train timetables for a rail corridor with given time-varying origin-to-destination passenger demand matrices. Given predetermined train skip-stop patterns, a unified quadratic integer programming model with linear constraints is developed to jointly synchronize effective passenger loading time windows and train arrival and departure times at each station. A set of quadratic and quasi-quadratic objective functions are proposed to precisely formulate the total waiting time under both minute-dependent demand and hour-dependent demand volumes from different origin–destination pairs. We construct mathematically rigorous and algorithmically tractable nonlinear mixed integer programming models for both real-time scheduling and medium-term planning applications. The proposed models are implemented using general purpose high-level optimization solvers, and the model effectiveness is further examined through numerical experiments of real-world rail train timetabling test cases.     

基于CAXA软件的曲线台阶数控加工方法研究

本文以CAXA自动编程软件为基础,以泵盖曲线台阶面加工为例,研究平面轮廓加工法、参数线加工法、平面区域加工法和自动区域加工法,提出了该类台阶面数控加工的最佳方案。     

铁路分局装车计划智能决策支持系统

在分析了铁路分局日间装车计划工作的特点后,指出掌握车流信息只是装车计划的基础,应建立装车计划智能决策支持系统(IDSS).铁路分局每日的装车计划要考虑装运货物的经济效益,文中提出了装车计划优化数学模型,据此来审批承认车,提高运输经济效益.     

结构化程序设计方法与面向对象的程序设计方法的比较

随着计算机的硬件及通讯技术的发展,计算环境发生了深刻的变化.计算环境的变迁和不断增长的软件需求对程序设计方法学提出了一个又一个的挑战,程序设计方法学也在挑战中前进.首先回顾软件工程程序设计方法的发展历史,指出结构化和面向对象是软件工程程序设计方法中的2个核心思想,分析、探讨了结构化程序设计方法与面向对象的方法的区别,并就如何在实践中正确应用给出了一些建议.     

BusinessObjects脚本程序在信息管理系统中的应用

主要阐述数据分析软件BusinessObjects中脚本程序的编写、调试、运行以及在MIS软件开发中的调用方法,并针对铁路十八点统计分析通用系统给出了具体的应用说明.