Awesome machine learning for combinatorial optimization papers.
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Updated
May 9, 2025 - Python
Awesome machine learning for combinatorial optimization papers.
A research protocol for deep graph matching.
A PyTorch library for all things Reinforcement Learning (RL) for Combinatorial Optimization (CO)
A Python Graph Matching Toolkit.
Code for the paper 'An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem' (INFORMS Annual Meeting Session 2019)
The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation net…
An OpenAi Gym environment for the Job Shop Scheduling problem.
Parallel Tabu Search and Genetic Algorithm for the Job Shop Schedule Problem with Sequence Dependent Set Up Times
Implementation of ECO-DQN as reported in "Exploratory Combinatorial Optimization with Reinforcement Learning".
L2O/NCO codes from CIAM Group at SUSTech, Shenzhen, China
[ICML 2024] "MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts"
[NeurIPS 2023] T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization
Learning 2-opt Heuristics for the TSP via Deep Reinforcement Learning
A Hyper-Heuristic framework
Solving tsp (travel sales problem) using ruin & recreate method.
[IROS 2024] EPH: Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding
Large Neighborhood Search based on Neural Construction Heuristics
Code accompanying the paper "Learning Permutations with Sinkhorn Policy Gradient"
SAT-based, MILP, and belief propagation preimage attacks on SHA-256 and other cryptographic hash functions
Modelling and Solving Employee Shift Scheduling (Including Nurse Rostering) Problems Using Constraint Programming (Combination of Artificial Intelligence and Operations Research) and Software Engineering Technologies 应用约束规划(人工智能+运筹学)及软件工程技术建模和解决员工排班(包括护士排班)调度问题
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