基于遗传算法的城市公交骨架线网优化设计

摘要

Aiming at the common phenomenon that lacking of hierarchical quality of the urban public transit network design, this paper put forward a new method about building the urban public transit skeleton-network, then it built an optimization model of urban public transit skeleton-network, which could achieve the dual goals of maximizing the accessibility of the network and the direct traveler density of the public transit. It improved the genetic algorithm to resolve the model. In order to adjust the convergence rate, the algorithm defined the fitness by introducing dynamic punish coefficient. It also utilized the crossover probability and mutation probability by adaptive mechanism to adjust the searching space. At last, the calculating example shows that the new genetic algorithm performs a better optimization-searching function than the traditional ones.%针对现有城市公交线网设计时普遍存在缺乏层次性规划的问题,提出了城市公交骨架网络的布局方法,构建了以线网直达客流密度与线网可达性最大为双目标的公交骨架线网优化模型,设计了一种改进的遗传算法.该算法通过引入动态惩罚系数确定适应度,以调整收敛速度;通过自适应机制确定交叉概率和变异概率,以调整搜索空间.算例分析的结果表明本算法比传统遗传算法具有更好的寻优性能.