北京交通大学学报2025，Vol.49Issue(1)：90-99,10.DOI:10.11860/j.issn.1673-0291.20240034
基于仿真的地铁货运网络布局优化方法研究
Research on the optimization method for metro freight network layout based on simulation
摘要
Abstract
This study proposes a Metro Freight Network Layout Mathematical Optimization Model(MFNLMOM)to address the issue of urban freight transportation by utilizing the idle capacity of metro and suburban railway lines.It integrates metro,suburban railways,and road networks.First,a multi-objective mathematical optimization model for metro freight network layout is developed,com-prehensively considering factors such as transportation costs,node reconstruction and expansion costs,investment expenses,transfer frequencies,and carbon emission costs.The model aims to mini-mize overall freight costs and transportation time.Next,passenger flow,freight flow,and metro op-eration logic modules are designed and simulated using Anylogic software to obtain transfer arc seg-ment data within the freight network.Finally,the Gurobi mathematical optimization solver is em-ployed to allocate freight network traffic flow.This is followed by a sensitivity analysis of carbon emis-sion costs,transfer costs,and trans-portation costs.The research findings demonstrate that,com-pared to traditional road transportation schemes,the metro freight network demonstrates significant ad-vantages,reducing total costs by 55.08%and transportation time by 44.24%.Additionally,compared to the full-station transfer model,the MFNLMOM partial-station transfer model achieves higher com-putational efficiency.关键词
综合运输/网络布局/Gurobi数字优化求解器/Anylogic仿真/地铁货运Key words
integrated transportation/network layout/Gurobi mathematical optimization solver/Any-logic simulation/metro freight分类
交通运输引用本文复制引用
胡文虎,殷玮川,胡琳..基于仿真的地铁货运网络布局优化方法研究[J].北京交通大学学报,2025,49(1):90-99,10.基金项目
国家自然科学基金(62102032) （62102032）
北京市教育委员会科技/社科计划项目(KM202211417010) National Natural Science Foundation of China(62102032) （KM202211417010）
R&D Program of Beijing Municipal Education Commission(KM202211417010) （KM202211417010）
