TNQINGYUN's repositories
GA-NSGA
主程序 overall.m
pySOT
Surrogate Optimization Toolbox for Python
Routed-Dynamic-Bus-Scheduling-and-Allocation
We developed a dynamic Bus scheduling and Allocation system in collaboration with public transit service BEST operating in Mumbai, India. The given system provides three different methods for forecasting bus schedules for the next week (ARIMAX, SARIMAX, LSTM RNNs) and results in automation of services with better utilization of buses across Mumbai. The product has been developed after discussions with the public bus transport service in Mumbai, India. The system takes spreadsheet files containing all the data related to daily bus operations and generates forecasts for number of trips required on each route and per hour. Using these forecasts, we generate Bus Timetables and schedules with maximal reuse and minimal waiting time for passengers. The technologies used are python for business logic and back-end framework while PyQt framework was used for developing the GUI. Libraries used are Keras, Pandas and Statsmodel for developing the LSTM RNNs and statistical models (ARIMAX and SARIMAX) respectively.
TransitNetworkDesign
Transit Network Design Instances for Research
TransportationNetworks
Transportation Networks for Research
VI-Solver
Variational Inequality Solvers in Python