摘要
为减少煤矿井下燃油运输车辆的尾气污染,降低能耗并控制运输成本,在考虑巷道坡度及车辆载重影响计算碳排放量的基础上,建立了车辆调度优化模型。该模型以运输总成本和碳排放量最小为目标,同时设计了基于动态拥挤度和启发式交叉算子的改进NSGA-II求解算法。实例仿真试验表明:多目标优化模型既可以保证煤矿企业的经济效益,也在一定程度上促进了节能减排。改进后的算法在总运输成本上平均节省超过4%,在碳排放量上最优值改进达到3.91%,表现出较好的求解性能。
In order to reduce exhaust pollution of fuel transport vehicles in underground coal mines,reduce energy consumption and control transportation costs,a vehicle scheduling optimization model was established on the basis of considering the influence of roadway slope and vehicle load to calculate carbon emissions.The model aims to minimize the total transportation cost and carbon emission.Meanwhile,an improved NSGA-II algorithm based on dynamic congestion degree and heuristic crossover operator is designed.The simulation results show that the multi-objective optimization model can not only guarantee the economic benefits of coal mining enterprises,but also promote energy saving and emission reduction to a certain extent.The improved algorithm can save more than 4%on average in the total transportation cost,and improve the optimal value of carbon emission to 3.91%,showing a good solution performance.
作者
侯成铭
HOU Chengming(School of Economics and Management,Anhui University of Science and Technology,Huainan Anhui 232001,China)
出处
《兰州工业学院学报》
2023年第2期88-93,共6页
Journal of Lanzhou Institute of Technology
基金
国家自然科学基金(61873004)。
关键词
井下燃油车
车辆调度
NSGA-II算法
多目标优化
underground coal mine fuel truck
NSGA-II algorithm
vehicle scheduling
multifactor optimization