<cite id="d9bzp"></cite>
<cite id="d9bzp"><span id="d9bzp"></span></cite>
<cite id="d9bzp"><video id="d9bzp"></video></cite><var id="d9bzp"></var>
<var id="d9bzp"><video id="d9bzp"><thead id="d9bzp"></thead></video></var>
<menuitem id="d9bzp"><video id="d9bzp"></video></menuitem>
<var id="d9bzp"></var><cite id="d9bzp"><video id="d9bzp"></video></cite>
<cite id="d9bzp"></cite>
<var id="d9bzp"></var>
<var id="d9bzp"></var>
<var id="d9bzp"><video id="d9bzp"><thead id="d9bzp"></thead></video></var>

公交车调度方案

时间:2017-08-11 数学毕业论文 我要投稿

公交车调度方案
摘要
     本文要求在照顾乘客和公交公司双方利益的前提下,给出1个合理的调度方案。此文以乘客的满意率、公交公司的满载率和所需车辆数目为目标函数,求它们的加权和的最大值。由于双方的利益是矛盾的,如何找到1个令双方都能接受的解是问题的关键。因此要找出与双方利益均密切相关的因素——发车间隔,通过对发车间隔的寻优,来解决这个问题。
     根据始发站的18个时段的客流量以及前后时段之间的客流比率来确定峰值的分类,通过该方法得出了上行客流峰值为5 个,其峰值区间为:5:O0--6:00 , 6:00--10:00 , 10:00--16:00 , 16:00--19:00 , 19:00--23:00 ;下行客流峰值为5 个,其峰值区间为:5:O0--7:00 , 7:00--10:00 ,10:00--15:00 , 15:00--19:00 ,19:00--23:00.
    在寻找发车间隔的过程中,针对各个时间段内始发站上车人数的不同将发车间隔按早晚高峰期、低谷期、中间期,分成4个时期,采用搜索算法进行求解。 结果为早高峰期发车间隔为2分钟、中间期为7分钟、晚高峰期为2分钟、低谷期为10分钟,上行方向和下行方向的对应时期发车间隔相等;根据发车间隔,得到两个始发站的发车时刻表;计算出所需的最多车辆数目为51辆,总车次为575次,乘客满意率为95%,满载率为59.03%;提供了1份详尽的调度方案并对其可行性进行了论证。
然后对模型进行了改进。方案是对原来划分的4个时期加以细化,计算出所需的最多车辆数目为47辆;总车次为432次;乘客满意率为92.24%;满载率为70.49%。接着讨论了各时间段的行驶速度不同的发车方案和加开区间车的方案。另外还进行了参数灵敏度分析,得到了不同的时期的发车间隔变化对于模型的影响程度,其中t1的影响程度最大。

关键字:公交车调度;加权求和;峰值;搜索算法


Abstract

This paper requirements in taking care of the passengers and transit interests of both companies on the premise that given a reasonable scheduling program. Quoting a customer satisfaction rate, the bus company loaded with the required rate and the number of vehicles as the objective function, They requested the weighted and the maximum. Because the two sides are conflicting interests, how to find a mutually acceptable solution is the key to the problem. Therefore to identify with the interests of both sides are closely related factors -- frequencies, the frequencies of the optimization, to solve this problem.
According to the sending station 18 hours and the customer flow between the periods before and after the passenger flow peak ratio to determine the classification, The methodology adopted by the rising passenger traffic for five peak, the peak interval : 5 : will be in -- 6 : 00, 6 : 00 -- 10:00, 10:00 -- 16 : 00, 16:00 -- 19 : 00, 19:00 -- 23 : 00; downlink peak passenger flow for the five, their peak interval : 5 : will be in -- 7 : 00, 7:00 -- 10 : 00, 10 : 00 -- 15:00, 15:00 -- 19 : 00 ,19:00 -- 23 : 00.
Find headway in the process, address the various periods sending 100101 number of different frequencies according to the peak sooner or later, the bottom view, in the middle period, divided into four periods, the search algorithm used to solve. Early results of the peak frequencies of 2 minutes, in the middle period of seven minutes, the evening peak period of two minutes, the bottom for 10 minutes, uplink and downlink direction of the direction of the corresponding period of the same frequencies; According headway, be sending two stations in question Schedules; calculate the maximum number of vehicles to 51, with a total of 575 vehicles. passenger satisfaction rate of 95%, with a rate of 59.03%; provide a detailed scheduling program and its feasibility is demonstrated.
Then the model improvements. Program is to the original period of four to be refined, calculate the maximum number of vehicles to 47; Total vehicle trips to 432 times; passenger satisfaction rate of 92.24%; full rate of 70.49%. Then discussed each time the speed of the program in question and processing open interval car program. It is also a parameter sensitivity analysis, a different time frequencies for model changes the extent of the impact, t1 with the greatest influence.
 Keywords : Bus scheduling; Weighted summation; Peak; Search Algorithm

公交车调度方案相关推荐
云南快乐十分哪个好_北京pK怎么玩-湖北快3怎么玩 许魏洲| 转生眼中的火影世界| qq| iu为雪莉守灵| 西班牙人| 汤姆克鲁斯| 三星note10| iu为雪莉守灵| 雪莉今日进行尸检| 孙海涛微博致歉|