摘要
为统筹利用高速铁路枢纽内的旅客运输资源,研究高速铁路枢纽内客运场站的分工问题。以枢纽内列车总作业时间最小和场站能力协调为优化目标构建多目标整数规划模型,通过设计增广ε-约束算法求解模型的近似非支配前沿。以郑州高速铁路枢纽为例展开实例分析,从定性和定量的角度分别对原有方案与优化方案的差异及能力适应性进行比较,验证模型及算法的可行性和有效性。结果表明,增广ε-约束算法可以为所提出模型寻找到高质量的代表性非支配解,所得出的优化方案能够降低枢纽内列车的作业时间,提高场站能力利用协调度,可为高铁枢纽地区扩能改造、能力优化等措施的决策提供可靠参考依据。
To make comprehensive use of the passenger transportation resources in a high-speed railway hub,this study explores the division of labor among passenger stations within a high-speed railway hub.Herein,a multiobjective programming model was developed with the objectives of minimizing the total train operation time and coordinating the capacities of the stations in the hub.The augmentedε-constraint algorithm was used to solve the approximate nondominated frontier of the model.Using the Zhengzhou high-speed railway hub as a case study,the differences between the existing plan and the optimized plan and their adaptabilities were qualitatively and quantitatively compared to validate the feasibility and effectiveness of the proposed model and algorithm.The results show that the augmentedε-constraint algorithm can identify high-quality representative nondominated solutions for the proposed model.Moreover,the optimized plan can reduce the train operation time within the hub and enhance the coordination of station capacity utilization.Thus,this study provides reliable references and reasonable suggestions for decision-making regarding capacity expansion,transformation,and optimization of high-speed railway hub areas.
作者
张杰
何世伟
赵日鑫
陈旻瑜
刘杰
ZHANG Jie;HE Shiwei;ZHAO Rixin;CHEN Minyu;LIU Jie(Operation Management Department,Shandong Railway Investment Holding Group Co.,Ltd.,Jinan 250014,China;Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China)
出处
《山东科学》
CAS
2024年第4期121-130,共10页
Shandong Science
基金
山东铁路投资控股集团有限公司科研项目(2022-SDRI-YY-0002)。
关键词
铁路运输
能力利用
多目标优化
高速铁路枢纽
车站分工
railway transportation
capacity utilization
multi-objective optimization
high-speed railway hub
division of labor among stations
