基于模拟退火-自适应布谷鸟算法的城市公交调度优化研究

为改善城市常规公交运营效率，提出基于模拟退火-自适应布谷鸟算法的公交调度优化模型。通过结合线路实际客流数据反映的客流特征，建立考虑公交公司和乘客双方利益的公交调度优化模型；改进布谷鸟算法固定步长并加入模拟退火算法退火操作，设计模拟退火-自适应布谷鸟算法，改善寻优过程中跳出局部最优解而全局寻优的能力；以福州125路公交线路为例，将该线路客流特征数据应用于模型和求解算法中。结果表明，基于不同利益方权重下通过模型算法计算出的结果均优于现有调度方案，验证了模型及算法的有效性及实用性。

Urban Bus Scheduling Optimization Based on Simulated Anneal-adaptive Cuckoo Search Algorithm

In order to improve the operation efficiency of urban public transport, a public transport scheduling optimization model based on the Simulated Annealing- adaptive Cuckoo Search algorithm is proposed. With the passenger flow characteristics reflected by the actual passenger flow data of the route, a bus scheduling optimization model considering the interests of both the bus company and passengers is established. By improving the fixed step size of the Cuckoo Search algorithm and adding the annealing operation of the Simulated Annealing algorithm, the Simulated Annealing- adaptive Cuckoo Search algorithm is designed to improve its ability to jump out of the local optimal solution and find the global optimization in the optimization process. Finally, taking the No.125 bus line in Fuzhou as an example, the passenger flow characteristic data of this line is applied to the model and the solution algorithm. The results show that the results obtained by the model algorithm based on different stakeholder weights are better than the existing scheduling scheme, which verifies the effectiveness and practicality of models and algorithms.