A public transit network optimization model for equitable access to social services

This repository contains raw data generated for use in Rumpf and Kaul 2021 (referenced below), and includes sets of files for defining transit networks as well as raw data tables generated by the solution algorithm. See the included README for an in-depth explanation of each data set. The main focus of the study was to develop and test a public transit design model for improving equity of access to social services throughout a city. The main case study was based on the Chicago Transit Authority network, with the goal of making minor alterations to the bus fleet assignments in order to improve equity of access to primary health care facilities. A small-scale artificial network was also generated for use in sensitivity analysis. The data sets in this repository include network files used by our hybrid tabu search/simulated annealing solution algorithm in order to solve the social access maximization problem (see the GitHub repository referenced below). Also included are the raw data tables from the CTA and artificial network trial sets. The results of this study indicate that it is indeed possible to significantly increase social service access levels in the least advantaged areas of a community while still guaranteeing that transit service remains near its current level. While improving the access in some areas does require that other areas lose some access, the gains are generally much greater than the losses. Moreover, the losses tend to occur in the areas that already enjoy the greatest levels of access, with the net result being a more even distribution of accessibility levels throughout the city.本仓库包含为Rumpf与Kaul 2021年研究（见下文引用）生成的原始数据，涵盖用于定义公共交通网络的文件集，以及由求解算法生成的原始数据表。请参阅随附的README文档，以深入了解各数据集的详细说明。 本研究的核心目标是开发并测试一款公共交通设计模型，用于优化城市范围内社会服务的可达性公平性。主要案例研究基于芝加哥交通局（Chicago Transit Authority, CTA）的公交网络，旨在通过小幅调整公交车队的分配方案，以提升前往初级医疗保健机构的可达性公平性。此外，研究团队还生成了小型人工网络，用于开展敏感性分析。 本仓库收录的数据集包含混合禁忌搜索/模拟退火求解算法在求解社会服务可达性最大化问题时所用的网络文件（详见下文引用的GitHub仓库）。同时还包含来自CTA网络与人工网络试验集的原始数据表。 本研究结果表明，在保障公共交通服务水平维持在当前基准附近的前提下，可切实大幅提升社区弱势区域的社会服务可达性水平。尽管部分区域的可达性提升需要以其他区域的部分可达性损失为代价，但整体收益通常远大于损失。此外，此类损失往往集中在原本已拥有较高可达性水平的区域，最终实现城市整体可达性水平分布更为均衡的目标。