公交车优化调度中的几个问题的研究

本文将 2 0 0 1 CMCM B题公交车调度的最优化问题分成两个相对独立的问题来讨论 ,由所要运送的乘客数来决定公交公司的最小车辆数 ,由乘客到达来决定发车时刻表 .我们求出了最小车辆数和一个可行的最优时刻表 .     

公交车调度问题的数学模型

对2001年全国大学生数学建模竞赛的B题－公交车调度问题进行了分析，建立了调度的目标规划模型及0－1规划模型。在假设各站上、下车人数服从均匀分布的条件下，通过对模型的求解，求出了公交公司的最小运行车辆数52辆，并给出了发车时刻表，其中上行方向运行225班次，下行方向运行220班次，该模型简单，求解容易，能较好地考虑各方利益。     

一类串行生产线的最优调度问题的注记

本讨论了[1]中串行生产线最优调度问题，给出了生产线生产周期的显示公式，对两个变量时最优调度的解的特性进行了研究。     

一类串行生产线的最优调度问题的注记

本文讨论了文［１］中串行生产线最优调度问题，给出了生产线生产周期的显示公式，对两个变量时最优调度的解的特性进行了研究．     

公交车高峰和平峰转换的调度研究

旨在对城市公共交通系统建立合理的数学模型,对公交车的调度进行合理规划,为城市建设提供借鉴作用.从深圳市的实际情况出发,建立了合理的公交运营调度模型,让公交的使用经济最大化、合理化.通过对大数据的合理分析,给出高峰和平峰的定义;通过对公交车的发车频率、运营所得的总收入与时间的关系的分析,给出高峰和平峰转换期的调度方案;借助OD矩阵,给出最大断面客流,从而完成对高峰和平峰的预测,并通过合肥市某公交线路的数据验证了此模型的正确性与广泛适用性.     

公交车调度问题的数学模型

对 2 0 0 1年全国大学生数学建模竞赛的 B题——公交车调度问题进行了分析 ,建立了调度的目标规划模型及 0— 1规划模型 .在假设各站上、下车人数服从均匀分布的条件下 ,通过对模型的求解 ,求出了公交公司的最小运行车辆数 5 2辆 ,并给出了发车时刻表 ,其中上行方向运行 2 2 5班次 ,下行方向运行 2 2 0班次 .该模型简单 ,求解容易 ,能较好地考虑各方利益     

车辆路径问题的混合优化算法

讨论了一类车辆路径调度问题(VRP)及其数学模型，并且分析了以遗传算法求解该类问题时的染色体表示和有关遗传操作，然后结合2-opt局部优化算法提出了GA with2-opt算法来求解VRP问题，试验结果说明了该算法的有效性和可行性。     

多车场有时间窗的多车型车辆调度及其禁忌算法研究

本文针对物流配送中的多车场车辆调度问题提出了两种多车场的处理方法，介绍了多车场车辆调度问题中容量、时间窗、多车型等多种约束的处理方法，并且根据具体约束情况设计了禁忌算法，对多车场有时间窗的多车型车辆调度问题加以实现，给出了一个具有代表性的算例试验结果和结果分析，通过试验表明了此方法对优化有时间窗的多车型车辆调度问题的有效性．     

车间作业调度的可行化判定及不可行解的纠正

生产调度过程中出现不可行解是调度研究经常遇到的问题之一.提出了对JSP调度方案进行可行化判定和纠正不可行解的可行算子,算子包括了基于有向图拓扑排序原理对车间作业调度方案进行可行判定的方法和将不可行解纠正为可行解的算法.证明了该纠正算法总能成功,并对算子的功能进行了拓展使之还可应用于不完备调度.最后讨论了可行算子的特点、时间效率和应用前景.     

基于遗传算法的多目标柔性工作车间调度问题求解

本文针对柔性工作车间调度问题给出了一个有意义的综合目标尽可能缩短制造周期的同时尽可能的减少机器负荷。由于传统遗传算法在多目标柔性工作车间调度问题上的局限性，我们提出了一种改进遗传算法：首先，我们给出了针对综合目标的工序调度算法获得初始集合；接着，针对柔性工作车间调度问题的特点，我们在常用的基于工序顺序的编码方法上融入了基于机器分配的编码方法，并据此设计了相应的交叉变异操作；最后借鉴了物种进化现象中的环境迁移思想设计了解决多目标优化问题的迁移操作。实验结果表明，改进的遗传算法在多目标柔性工作车间调度问题的解决上要优于传统遗传算法。     

公交网络时刻表再协同设计的多目标优化模型

为了改善公交服务质量,公交运营者试图调整现有时刻表的发车时间,使不同线路的车次协同到达换乘站点以方便乘客换乘。针对此场景,研究了公交时刻表重新协同设计问题,提出了求解该问题的多目标模型。模型考虑了对发车间隔灵敏的乘客需求、灵活的车次协同到站方式和发车时间的规则性,分析了该多目标模型的特征和计算复杂性,表明本文研究的问题是NP-hard问题,且它的帕累托最优前沿是非凸的,设计了基于非支配排序的遗传算法求解模型。算例表明,与枚举算法相比,提出的求解算法在较短的时间内可获得高质量的帕累托解。     

Estimating bus passenger waiting times from incomplete bus arrivals data

This paper considers the problem of estimating bus passenger waiting times at bus stops using incomplete bus arrivals data. This is of importance to bus operators and regulators as passenger waiting time is a key performance measure. Average waiting times are usually estimated from bus headways, that is, time gaps between buses. It is both time-consuming and expensive to measure bus arrival times manually so methods using automatic vehicle location systems are attractive; however, these systems do not usually provide 100% data coverage and missing data are problematical. The paper contributes to the general theory of estimating headway variance using incomplete data. Various methods for replacing missing buses or discarding spurious bus headways are compared and tested on different data sets.     

A fuzzy clustering approach to real-time demand-responsive bus dispatching control

Quick response (QR) to passenger needs is a key objective for advanced public transportation systems (APTS), and it has become increasingly important for contemporary metropolitan bus operations to gain a competitive advantage over private transportation. This paper presents a real-time control methodology for demand-responsive bus operations that respond quickly to passenger needs. The proposed method primarily involves two levels of functionality: (1) short-term forecasting of passenger demands using time-series prediction models, and (2) identification of service strategies coupled with the associated bus service segments using fuzzy clustering technologies in response to variances in passenger demand attributes and traffic conditions. The proposed bus operations method identifies the demand-responsive vehicle service strategies primarily according to the predicted up-to-date attributes of passengers’ demands, rather than deterministic passenger arrival rates, which were generally used in previous literature. In addition, the variation of traffic conditions along bus lines is considered in the proposed method. Results from numerical studies using real data of passengers’ demands, including passenger volume at each bus stop and the passenger origin-destination (O-D) patterns, are presented to demonstrate the effectiveness of the proposed method for real-world applications.     

公路客运监管的进化博弈分析

运用进化博弈理论研究公路客运监管问题,建立了公路客运监管问题的博弈模型,分析了公路客运车主和公路客运管理者之间的行为选择,得到了博弈方的复制动态方程,研究了博弈模型的进化稳定策略。探讨了影响进化稳定策略的因素。研究结果表明公路客运车主和公路客运管理者在有限理性基础上得到的进化稳定策略与博弈双方的收益、系统所处的初始状态有关,并根据所提出的博弈模型,提出了合理性建议。     

客运问题的进化博弈分析

构建了客运车主群体之间以及客运车主群体与客运管理部门之间的博弈模型及其复制动态方程,并对复制动态方程做了分析与讨论,得出了博弈模型中各博弈方的进化稳定策略,并根据所提出的博弈模型,提出了合理性建议.     

A model for setting services on auxiliary bus lines under congestion

In this paper, a mathematical programming model and a heuristically derived solution is described to assist with the efficient planning of services for a set of auxiliary bus lines (a bus-bridging system) during disruptions of metro and rapid transit lines. The model can be considered static and takes into account the average flows of passengers over a given period of time (i.e., the peak morning traffic hour). Auxiliary bus services must accommodate very high demand levels, and the model presented is able to take into account the operation of a bus-bridging system under congested conditions. A general analysis of the congestion in public transportation lines is presented, and the results are applied to the design of a bus-bridging system. A nonlinear integer mathematical programming model and a suitable approximation of this model are then formulated. This approximated model can be solved by a heuristic procedure that has been shown to be computationally viable. The output of the model is as follows: (a) the number of bus units to assign to each of the candidate lines of the bus-bridging system; (b) the routes to be followed by users passengers of each of the origin–destination pairs; (c) the operational conditions of the components of the bus-bridging system, including the passenger load of each of the line segments, the degree of saturation of the bus stops relative to their bus input flows, the bus service times at bus stops and the passenger waiting times at bus stops. The model is able to take into account bounds with regard to the maximum number of passengers waiting at bus stops and the space available at bus stops for the queueing of bus units. This paper demonstrates the applicability of the model with two realistic test cases: a railway corridor in Madrid and a metro line in Barcelona.     

基于遗传算法的公交智能调度与优化——以南岳衡山景区为例

南岳衡山(以下简称南岳)以“外秀于林,内秀于文”驰名中外,作为风景名胜区近几年游客人数不断攀升。本文利用遗传算法对景区内公交线路的调度模型进行求解。首先,根据景区现有的公共交通资源和旅客的出行规律,构建了以旅游公交营运成本、游客等待成本和游客流失成本三方面优化目标的模型;然后,使用线性加权方法实现对旅客与营运公司双方利益兼顾,进一步完善模型;最后,利用Matlab对实地调研数据的车辆调度方案求解。表明该模型改善了南岳景区旅游交通,满足游客的合理需求,提升了旅游公司经营策略,真正成为“寿岳独秀”的知名品牌。     

Analysis of vibration effects on the comfort of intercity bus users by oscillatory model with ten degrees of freedom

The paper analyzes the effects of vibrations on the comfort of intercity bus IK-301 users. Evaluation of vibration effects was carried out according to the criteria set out in the 1997 ISO 2631-1 standard for comfort in public means of transport. Comfort is determined for the space of a driver, passenger in the middle part of the bus and passenger in the rear overhang. Also, the allowable exposure time to vibrations in drivers for the reduced comfort criterion was determined according to the 1978 ISO 2631-1 standard. The bus spatial oscillatory model with ten degrees of freedom was developed for the needs of the analysis. Bus excitation was generated applying the Power Spectral Density of the asphalt-concrete road roughness, as described by the H. Braun model. The allowable vibration exposure time for the driver’s body decreases as the spring stiffness of the driver’s seat suspension system increases. Simulation was performed using the MATLAB software.     

Determination of the number and locations of time points in transit schedule design — Case of a single run

An analytical model for the determination of the number and locations of time points as well as the amount of slack times in transit schedule design is developed. The model considers a bus route with a special passenger demand pattern in which all boarding passengers coordinate their arrivals at each stop in such a way that they never miss their intended bus, and therefore designing the schedule separately a single run at a time, becomes possible. The model employs the dynamic programming method to deal with the trade-offs among various cost components associated with the schedule quantitatively, and yet is flexible enough to incorporate the existing rules of thumb as well as transit operators' policies. Numerical examples that illustrate the applications of the model are given. The model, although not quite applicable to bus routes with general passenger demand patterns, is useful in the analysis of the contributing factors to the design of an economical, reliable, and operational transit schedule, and is likely to be adaptable for more realistic cases.     

基于APC和GPS数据的青奥会期间南京公共交通的调度与优化

为了得到青奥会期间南京市合理有效的公交调度方案,本文针对青奥会场馆、运动员村、旅游点等附近的南京公共交通线路,建立模型与算法.首先,通过APC数据与GPS数据的匹配,对客流数据进行站点匹配预处理,根据已有客流量数据,训练小波神经网络,从而对客流分布情况进行预测,然后基于客流预测结果,采用有序聚类法,实现客流高低峰时段的合理划分.其次,详细分析调度问题的关键所在,以时段总发车次数和乘客等待时间两个因素作为目标函数,将时段最大、最小发车间隔和满载率等作为约束条件,提出基于APC和GPS的公交车辆辅助调度模型,通过遗传算法对模型进行求解,得出不同时段的发车间隔和配车次数,并对模型的性能进行评估.以南京市D7路公交运营线路的实际客流数据为例,采用MATLAB软件进行仿真实验,得出优化结果.结果表明所建模型是合理的,从而为调度时刻表的生成提供了科学的依据.