绿色导向下供需协同的城轨列车开行方案优化OA

To address the issues of underutilized transport capacity,low passenger demand satisfaction,and high enterprise operating costs caused by unreasonable train operation plans,this study proposes a supply-demand coordinated train operation plan for urban rail transit based on the principle of traffic resource optimization allocation.Incorporating passenger travel behaviors and travel preferences,a multi-objective optimization model is established.The objectives are to maximize train supply-demand coordination,minimize the total passenger travel costs,and minimize the total enterprise operating costs.The model is subject to constraints such as carbon emissions,train departure frequency and line throughput capacity.An adaptive annealing-whale optimization algorithm is designed to solve the model,and its effectiveness is verified through a case study.The results show that,compared to the full-length route with multi-type formation,short-turn route with short formation,and short-turn route with long formation models,the short-turn route with multi-type formation model not only optimizes carbon emissions but also improves train supply-demand coordination by 185.92,53.15 and 36.07,respectively.It also reduces the total passenger travel costs by 17.8%,11.45%and 8.34%,and decreases the total enterprise operating costs by 29.09%,5.67%and 4.97%,respectively.Furthermore,compared with the whale optimization algorithm and simulated annealing algorithm,the proposed adaptive annealing-whale optimization algorithm improves the fitness value by 7.55%and 5.65%,and convergence speed by 4.46%and 7.55%,respectively,while optimizing all objectives.Therefore,the proposed model effectively enhances passengers,enterprise costs as well as carbon emissions,enhances supply-demand coordination.The designed algorithm demonstrates high solution performance in satisfying the model's requirements.