改进人工蜂群算法的农村DRT路径优化研究-《郑州大学学报(工学版)》

文章信息/Info

Title:: Research on Rural DRT Model ba＜x＞sed on Adaptive Large Neighborhood Search Artificial Bee Colony Algorithm

摘要:: 农村地区的需求响应公交模式因其特殊的运输特性区别于常规公交模式。本文根据农村客运出行的特殊规律和实际需求情况,对农村地区DRT模式进行了探讨，提出了考虑农村居民同时接送条件的车辆路径问题模型。在模型中考虑同时接送乘客的特殊时间窗和其他限制条件，构建了以运输网络总成本最优为目标的VRP模型，并提出了一种两阶段的自适应大邻域人工蜂群算法进行求解。最后通过实际算例仿真来验证该模型和算法的可行性。结果显示，农村地区需求响应公交模型在考虑同时接送的条件下更贴合实际情况，优化结果良好；另外，相比于遗传算法和ALNS算法，自适应大邻域人工蜂群算法收敛速度更快，成本均值、标准差和方差结果更优，在精度和鲁棒性上有较好的表现，可以有效地找到高质量解决方案。

Abstract:: The demand response public transport mode in rural areas is different from the conventional bus mode due to its special transport characteristics. According to the special rules of rural passenger travel and the actual demand, this paper discusses the DRT mode in rural areas, and puts forward a vehicle routing problem model considering the conditions of rural residents simultaneous transfer. Considering the special time window and other constraints, a VRP model with the goal of optimizing the total cost of transportation network is constructed, and a two-stage adaptive large neighborhood artificial bee colony algorithm is proposed to solve the problem. Finally, the feasibility of the model and algorithm is verified by a practical example. The results show that the demand response public transport model in rural areas is more suitable for the actual situation under the condition of considering simultaneous pick-up and drop off, and the optimization result is good in addition, compared with genetic algorithm and ALNS algorithm, the adaptive large neighborhood artificial bee colony algorithm has faster convergence speed, better cost mean, standard deviation and variance results, and has better performance in precision and robustness, and can effectively find high quality solutions.