控制理论与应用2024，Vol.41Issue(6)：1101-1110,10.DOI:10.7641/CTA.2023.20624
通勤合乘路径优化模型与算法
Commuting rideshare routing optimization model and algorithm
摘要
Abstract
The increase in road vehicles has led to increasingly serious urban traffic and environmental problems.Ride sharing is considered an effective way to reduce traffic congestion and reduce carbon emissions.Especially under the continuous impact of the corona virus disease 2019(COVID-19),commuters are more willing to use mutual assistance to travel.Considering the urgency of commuting time,commuters have commuting pressure and uncomfortable feeling of ride-sharing.In the absence of economic benefits,limits the matching range of ride-sharing routes,and adds penalty factors to improve the success rate of ride-sharing matching.In order to solve the larger scale problem,a greedy heuristic algorithm based on the optimal time interpolation is proposed,and three perturbation factors are added to improve the global search ability.Multiple groups of cases with different scales are used to test the disturbance effect.The results show that the designed algorithm can solve better results in a short time,and is more competitive than the exact algorithm,particle swarm algorithm and genetic algorithm in solving large-scale problems.In addition,the effect of ride-sharing can be improved by selecting employees who are far away and evenly distributed as pick-up.关键词
交通工程/共享合乘/路径优化/启发式算法/通勤出行Key words
traffic engineering/rideshare/route optimization/heuristic algorithm/commuting引用本文复制引用
李旺,柳伍生,肖义萍,李薇,周清..通勤合乘路径优化模型与算法[J].控制理论与应用,2024,41(6):1101-1110,10.基金项目
国家自然科学基金面上项目(61773077),长沙市自然科学基金项目(kq2202211),湖南省教育厅重点项目(21A0202),长沙理工大学研究生科研创新项目(CXCLY2022025)资助.Supported by the National Natural Science Foundation of China(61773077),the Natural Science Foundation of Changsha(kq220221),the Research Foundation of Education Bureau of Hunan Province,China(21A0202)and the Postgraduate Scientific Research Innovation Project of Changsha University of Science and Technology(CXCLY2022025). （61773077）
