Graph Reinforcement Learning for Network Control via Bi-Level Optimization

Official implementation of "Graph Reinforcement Learning for Network Control via Bi-Level Optimization"

Prerequisites

You will need to have a working IBM CPLEX installation. If you are a student or academic, IBM is releasing CPLEX Optimization Studio for free. You can find more info here

To install all required dependencies, run

pip install -r requirements.txt

Important: Take care of specifying the correct path for your local CPLEX installation. Typical default paths based on different operating systems could be the following

Windows: "C:/Program Files/ibm/ILOG/CPLEX_Studio128/opl/bin/x64_win64/"
OSX: "/Applications/CPLEX_Studio128/opl/bin/x86-64_osx/"
Linux: "/opt/ibm/ILOG/CPLEX_Studio128/opl/bin/x86-64_linux/"

Contents

• supplychain/: Code to reimplement Supply Chain Inventory Management experiments (Section 5.2).
• mobility/: Code to reimplement Dynamic Vehicle Routing experiments (Section 5.3).

Please refer to the respective README.md files for further details about the usage of both sub-directories.