Leo

End-to-end-DRL-for-FJSP. This is the official code of the publised paper 'A Multi-action Deep Reinforcement Learning Framework for Flexible Job-shop Scheduling Problem'

DRL-and-graph-neural-network-for-routing-problems. This is the official code for the published paper 'Solve routing problems with a residual edge-graph attention neural network'

RL-100. [Science Robotics 2026] Official Implementation of the paper RL-100

Dispatching-rules-for-FJSP. This is the official code for the baseline methods of the publised paper 'A Multi-action Deep Reinforcement Learning Framework for Flexible Job-shop Scheduling Problem'

FJSP-benchmarks. The public benchmark instances of flexible job shop scheduling problem

Uni-O4. Author's Pytorch implementation of our ICLR 2024 paper "Uni-O4"

MIP-model-for-FJSP-and-solved-by-Gurobi. the mixed-integer programming model for flexible job shop scheduling problem is solved by gurobi

FJSPDRL. The code and data will be published after accepting our paper

leikun-starting.

koptimizer.

zcaicaros.

paper. Reading List

leikun-start.github.io. Personal website

Lei-Kun.github.io. https://Lei-Kun.github.io/

mnist_challenge. A challenge to explore adversarial robustness of neural networks on MNIST.

ReinFlow. Official Implementation of ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning (RL)

BPPO. Author's Pytorch implementation of ICLR2023 paper Behavior Proximal Policy Optimization (BPPO).