Combinatorial Optimization Python Packages

ortools

Google's Operations Research tools:

fjsplib

Python package to read and write instances for the flexible job shop problem.

aegypti

Aegypti: Triangle-Free Solver

ferrotherm

Thermodynamic computing in pure Rust: energy-based models, block-Gibbs, parallel tempering, thermodynamic linear algebra, stochastic differentiable programs, a variational compiler onto device topologies, and a joules ledger. Zero deps, wasm-clean, verified against exact physics — and it reaches real Ising silicon through the same trait as a CPU.

annealbridge

Optimization middleware for AI agents — describe the problem as JSON, get verified, ranked solutions over MCP, CLI or Python.

accelbrainbeat

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 networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

packvium

Deterministic 3D cartonization and bin packing for Python. Exact integer geometry, no dependencies.

submodlib-py

Summarize Massive Datasets using Submodular Optimization

rl4co

A PyTorch library for all things Reinforcement Learning (RL) for Combinatorial Optimization (CO)

pysummarization

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 networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

neoma-pcam

NEOMA: Real-time Physical AI & Edge Appliance powered by P-CAM (0.72ms Latency & Silicon SEAL Verification)

graphfla

A graph-based python framework for fitness landscape analysis

pydbm

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 networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

accel-brain-base

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 networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

numberpartitioning

Pure Python solver for the multi-way partition problem

geco

Generators for Combinatorial Optimization

qqa

Quasi-Quantum Annealing (QQA): a GPU solver for combinatorial & spin-glass optimisation — PyTorch library + live Streamlit dashboard. ICLR 2025.

pyqlearning

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 networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

sll-core

SLL-Core: PyTorch library for automatic differentiation through discrete operations via Static Local Linearization.

jinete

High Performance solving suite for the Pickup and Delivery Problem and its related extensions.

pygan

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 networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

tspgrasp

A Greedy Randomized Adaptive Search Procedure (GRASP) for the Traveling Salesman Problem (TSP)

tspy

An optimization package for the traveling salesman problem

jssenv

An OpenAi Gym environment for the Job Shop Scheduling problem.