This repository contains the source code described in "Connected population synthesis for transportation simulation"(Zhang D., Cao J., Feygin S., Tang D.and Pozdnoukhov A., Connected population synthesis for transportation simulation. (published in Transportation Research Part C: Emerging Technologies), 2019)(pdf on ssrn)
The connected population synthesis pipeline consists of three steps:
Composition and socio-economic char- acteristics of the synthetic households are generated based on Bayesian network parameters estimated from a typical household survey data
We utilized R bnlearn package for bayesian networks parts.Please check bnlearn notebook
We implemented our algorithm using CPLEX Python API, please check the source code packaged in Python class. We also implemented the parallel version using Python multiprocessing, please check the source code packaged in Python class
We also provided the ipython notebooks as examples. Please check non parallel version and parallel version
We implemented the community-distance ERGM model using CVXPY, please check the source code packaged in Python class. We also provided the ipython notebook as examples. Please check the example with synthetic data. Due to data privacy issues the data for the paper isn't relesed
This project is licensed under the MIT License