基于模糊蚁群算法的城轨交通网络节点分配优化策略

Optimization strategy of urban rail transit network node allocation based on fuzzy ant colony algorithm

针对城轨交通发展规划中节点设置分配的实际需求,文中提出了一种基于模糊蚁群算法的交通网络节点分配优化策略.为了兼顾节点辐射能力与网络效率,该策略通过利用模糊系数构造非线性最大化目标函数,将多目标非线性优化问题转化为节点属性识别和最优路径问题.针对节点属性识别,本文利用灰色关联模糊映射方法计算区域中心的模糊隶属度,并利用模糊判决方法判决节点属性.在此基础上本文采用蚁群算法搜索全局最优路径,确定网络节点最优配置方案.仿真实验和分析结果说明,相比于现有算法,文中所提算法具有更高的节点辐射能力和全局网络效率,且在迭代40次之后性能逐渐收敛,达到最优解.

According to the actual needs of node setting and allocation in urban rail transit development planning,a transportation network node optimization strategy based on fuzzy ant colony algorithm is proposed in this paper.In order to take into account the node radiation capacity and network efficiency,the strategy constructs a multi-objective nonlinear optimization problem by using fuzzy coefficients,and transforms the multi-objective nonlinear optimization problem into node attribute identification and optimal path problem.For the node attribute identification,this paper uses fuzzy mapping method based on grey correlation to calculate the fuzzy membership of the regional center,and judges the node attribute with the fuzzy decision method.On this basis,this paper uses ant colony algorithm to search the global optimal path to determine the optimal configuration scheme of network nodes.Simulation experiments and analysis results show that compared with the existing algorithms,the proposed algorithm has higher node radiation ability and global network efficiency.In addition,the performance of the algorithm converges gradually after 40 iterations to reach the optimal solution.