时变路网下考虑碳排放的需求响应型公交调度优化模型

Demand-responsive bus scheduling optimisation model considering carbon emissions under time-varying road network

以往对需求响应型公交的研究中,鲜有考虑到时变路网、碳排放等因素对车辆调度的影响,需要对现有研究的局限性进行改进。针对当前“双碳”背景下存在传统燃油公交与电动公交混合运行的现状,结合两者特性分别给出约束条件、成本和碳排放测算方法,建立包含延误时间、碳排放和运营成本作为优化目标的调度优化模型,并提出了自适应遗传-萤火虫算法用以求解该模型。实验结果表明:a)所提算法改善了传统遗传算法中易陷入局部最优的问题,在基于仿真路网的实验中能使目标函数减少9.1%,平均车辆使用数、平均途经节点数和平均行驶里程数分别减少了0.3辆、4.9个和104.57 km,提高了求解精度;b)模型考虑碳排放影响最高能减少9%的碳排放量,运营成本降低2.9%;c)动态阻抗下的车辆调度方案既贴近实际情况,又能同时降低7.5%的碳排放以及节约5%的运营成本;d)电动公交的引入能得到显著的碳减排效果,但由此带来的成本上升也是不容忽视的。

Previous studies on demand-responsive buses rarely considered the impact of time-varying road networks and carbon emissions on vehicle scheduling,indicating the need for improvement in the limitations of existing studies.In response to the current scenario of mixed operation involving traditional fuel buses and electric buses under the backdrop of“dual-carbon”,this study outlined constraints,costs,and methods for measuring carbon emissions based on the characteristics of these two types of buses.It established a scheduling optimization model that incorporates delay time,carbon emissions,and operational costs as optimization objectives,it proposed the use of an adaptive genetic-firefly algorithm.The experimental results show that:a)The proposed algorithm addresses the issue of local optimality common in traditional genetic algorithms.In experiments based on a simulated road network,it achieves a 9.1%reduction in the objective function,along with decreases of 0.3 vehicles,4.9 nodes,and 104.57 km in average vehicle usage,average route nodes,and average travel distance respectively,enhancing the precision of the solution.b)Considering the impact of carbon emissions,the model can achieve a maximum reduction of 9%in carbon emissions and a 2.9%reduction in operating costs.c)The vehicle scheduling scheme under dynamic impedance is both realistic and achieves simultaneous reductions of 7.5%in carbon emissions and 5%in operating costs.d)The introduction of electric buses yields a significant reduction in carbon emissions,but the associated cost increase is noteworthy.