摘要
研究城市公交车调度优化问题,根据公交车辆排班和调度运行要求,兼顾到乘客和公交公司的利益,为优化服务目标,建立了基于遗传算法的公交智能排班调度模型。采用以发车时刻为变量的真实值编码方法,在构造适应度函数时,用惩罚函数法将多种约束条件加到目标函数上,简化了计算量。进行仿真实验,结果证明,利用改进的遗传算法求解,可以得到不均匀发车优化时刻表,并能为公交智能排班优化提供较大搜索空间,提高了实际运行效率。
The model of intelligent schedule of public traffic vehicles based on the Genetic Algorithm is established according to the characteristics of the public transportation vehicles＇ scheduling and the Genetic Algorithm,giving attention to the benefits of the passengers and agency.It adopts the true value of the coding method using the start time as the variable and uses the penalty function method to add a variety of constraints to the objective function when constructing the fitness function,which simplifies the calculation.Finally,the simulation results are obtained by using the improved Genetic Algorithm for solving the non-uniform grid schedule.Results show that the improved Genetic Algorithm can find the approximate best result in the huge search space of optimization,and greatly increased the computational efficiency.
出处
《计算机仿真》
CSCD
北大核心
2011年第3期345-348,404,共5页
Computer Simulation
关键词
智能排班
遗传算法
适应度函数
惩罚函数
行车时刻表
Intelligent schedule
Genetic algorithm
Fitness function
Penalty function
Start schedule
