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摘要：随着近几年来对铁路运输的需求量越来越大，铁路也在这几年中发展得越来越快，而传统的铁路运行速度较低，能耗较大，同时，列车的运行过程中，在保证运行的安全性基础上，还需要考虑乘客的舒适性，因此需对列车的运行过程进行优化。本论文采用单质点运动模型，对列车的区间运行过程进行建模。在运行过程中，采用牵引、惰行和制动三种控制策略，在列车运行时间、运行距离和速度的约束条件下，分别以运行的时间准点率、列车停靠的准确率和运行能耗为优化目标， 再以三种优化目标的加权平均值作为系统的总优化目标， 建立了多目标列车运行优化模型。 在求解该优化问题时， 采用粒子群优化算法，在确定的工况条件下，对各工况的运行距离进行优化。仿真结果证明了其有效性。20714
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毕业论文关键词：粒子群优化算法；多目标；能耗
Train Operation of Multi-Objective Optimization
Abstract: In recent years, the demand for railway transportation is increasing and the railway
transportation has been developed faster and faster. The traditional railway has lower speed and
much more energy. During the operation of the train, not only we should ensure the safety of
operation but also consider the comfort of the passengers. Therefore we need to optimize the
operation of the train. In this paper, the single particle motion model is adopted and builds a
model to describe the interval operation of the train. During the operation, there are three
control strategies such as traction, coasting and braking. Under the conditions of the train
running time, running distance and speed, we use the punctuality of running time, the accuracy
of the train stopping and energy consumption to be the goal of optimization. And then we use
the weighted average of these three optimization goal to be the overall optimization goal, and
build a multi-objective optimization train model. In solving the optimization problem, we use
particle swarm optimization to optimize the distance of running conditions under certain
operating conditions. The results of the simulation proved its effectiveness.
Key Words：Particle Swarm Optimization; multi-objective; energy
目录
1 引言 . 1
1.1 本课题的目的和意义 .. 1
1.2 国内外研究现状 . 1
1.3 发展趋势 . 2
1.4 研究内容 . 3
2 列车运行优化问题建模 .. 4
2.1 列车受力分析 .. 4
2.1.1 牵引力 4
2.1.2 基本阻力 .. 4
2.1.3 附加阻力 .. 4
2.1.4 制动力 5
2.1.5 合力 . 5
2.2 列车运行的单质点模型 . 5
2.2.1 能耗指标 .. 6
2.2.2 时间指标 .. 6
2.2.3 停靠性指标 . 7
2.3 多目标优化模型 . 7
3 智能优化算法 9
3.1 遗传算法 . 9
3.2 蚁群算法 .. 10
3.3 粒子群优化算法 .. 10
4 基于粒子群的多目标优化仿真程序设计 .. 13
4.1 列车运行过程建模 . 13
4.2 粒子群优化算法设计 16
4.3 程序调试及运行结果 18
4.3.1 列车程序具体运算过程 18