改进人工蜂群算法的农村DRT路径优化研究

Research on Route Optimization of Rural DRT Based on Improved ABC Algorithm

农村地区居民的出行需求低且分布分散,导致常规公交运营难以为继。针对农村公交运营成本高、运输效率低的问题,基于农村居民出行需求特征,构建了考虑农村地区需求响应公交(DRT)同时接送模式的车辆路径问题模型,提出一种改进的两阶段自适应大邻域人工蜂群算法(adaptive large neighborhood search artificial bee colony algorithm,ALNS算法)对模型进行求解。算例结果分析显示:在低需求密度的农村地区,农村DRT同时接送模型更具经济性和实用性;相比于遗传算法和自适应大邻域搜索算法,改进的人工蜂群算法成本均值分别比上述2种算法结果低9%和3%,且收敛速度更快、在精度和稳定性上表现更优,可以有效地找到高质量的最优方案。

The travel demand of residents in rural areas is low and scattered,which makes it difficult for conventional bus mode to sustain.According to the characteristics of rural residents′travel demand,in order to reduce the operation cost and improve the transportation efficiency,a vehicle routing problem model considering the demand responsive transit(DRT)simultaneous pick-up and drop off mode in rural areas was constructed.And an improved two-stage adaptive large neighborhood search artificial bee colony algorithm was proposed to solve the model.The example results showed that in the rural areas with low demand density,the rural DRT simultaneous pick-up and drop off model was more economical and practical.Compared with the genetic algorithm and adaptive large neighborhood search algorithm,the average cost of the improved artificial bee colony algorithm was 9%and 3%lower than the above two algorithmsrespectively,and the convergence speed was faster,the performance was better in accuracy and stability,so it could effectively find the optimal solution with high quality.