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a-feasible-solution-for-rebalancing-large-scale-bike-sharing-systems

alonso-mora

Pooled fleet dispatching by Alonso-Mora et al. (2017) for MATSim

amod-toolkit

A reference implementation of the time-varying, charge-aware network flow model for AMoD systems. Code for On the Interaction between Autonomous Mobility on Demand Systems and Power Distribution Networks -- An Optimal Power Flow Approach

amodeus

Autonomous Mobility-on-Demand Extremely Useful Simulation

aviz

Animates vehicle fleet routing traces using JS + Mapbox.

bicycle-rebalancing-optimization

Statistical and optimization model using historical data to predict expected number of bike arrivals and departures at each station and based on real time demand and supply, calculate the optimal way to rebalance all bikes across network stations.

bikerebalancing

Simulations of the paper entitled `Spatial-Temporal Inventory Rebalancing for Bike Sharing Systems with Worker Recruitment`

bikeshare-boston

bixi-optimization

Route optimization for bike rebalancing within the BIXI bike-sharing system

bss-optimization

Creating a optimization model for the bike sharing rebalancing problem using python and mip.

business_solution_final_capstone_bike_sharing

My Final Capstone for Thinkful's Data Science Course - predicting the rebalancing needs of a Bike Sharing Company.

citi-bike-rebalancing-simulation-and-modeling

This project was done during my education at Stevens Institute of Technology with collaboration between me and Pro. Paul T. Grogan. The project is about applying Discrete Event simulation used Simpy library(MIT License) to model the Citibike Rebalancing system.

citibike

Predicting Citi Bike trip demand and analyzing need for bike rebalancing

comp6651

Bike Sharing Rebalancing Problem Solution by Greedy Heuristic Algorithm, Greedy Algorithm and K-means Clustering Algorithm

cplex-bikesharingrebalancingproblem

A CPLEX implementation to solve the specific problem of Bike Sharing Redistribution

gnn-rl-for-amod

Code for Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems

gr-madrl-amod

Code for Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems

matsim-amod

A fork of MATSIM's DVRP module for rebalancing of self-driving vehicles in an Autonomous Mobility on Demand (AMoD) framework

matsim-maas

This project contains a collection of examples to run (Autonomous) Mobility as a Service in MATSim.

mit-15.072-bike-rebalancing

This project was conducted during the MIT 15.072 Analytics Edge course (Fall 2020).

mixed-fleet-mod

This repository consists of codes to control a mixed fleet of autonomous and human-driven vehicles providing Mobility-on-Demand services.

offline-rl-for-amod

Code for Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning

pamod

Code for On the interaction between Autonomous Mobility-on-Demand systems and the power network: models and coordination algorithms

pso-bikesharingrebalancingproblem

An implementation of the Particle Swarm Optimization method applied to the specific problem of Bike Sharing Redistribution

rebalancing-bike-sharing

Mathematical Model used for the rebalancing problem in bike-sharing system

rebalancing-bike-sharing-system-dashboard

rebalancing-optimization-for-bike-sharing-systems

rebalancing_minimizer

a tool that can predict a proposed Bike Share Toronto station's burden on the rebalancing team, using the proposed station's longitude, latitude, and elevation

robust-optimization-using-machine-learning-for-building-uncertainty-sets

Built uncertainty sets for demand forecasting of Hubway bikes and solved the optimization problem of bike rebalancing within stations.

slevels

Autonomous mobility-on-demand system routing application with on-demand hiring and service-level contracts.