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

submodlib-py

Summarize Massive Datasets using Submodular Optimization

rl4co

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

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.

numberpartitioning

Pure Python solver for the multi-way partition problem

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.

sll-core

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

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.

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.

jinete

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

pydbm

`pydbm` is Python library for building Restricted Boltzmann Machine(RBM), Deep Boltzmann Machine(DBM), Long Short-Term Memory Recurrent Temporal Restricted Boltzmann Machine(LSTM-RTRBM), and Shape Boltzmann Machine(Shape-BM). From the view points of functionally equivalents and structural expansions, this library also prototypes many variants such as Encoder/Decoder based on LSTM, Convolutional Auto-Encoder, and Spatio-temporal Auto-Encoder.

geco

Generators for Combinatorial Optimization

tspgrasp

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

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.

graph-stitcher

This tool is a little framework to determine possiblemerges between two graphs based on a set of requiredadditional relationships (aka as stitches / edges).

qqa

Quasi-Quantum Annealing (QQA): a general-purpose GPU solver for combinatorial and spin-glass optimization, with PI-GNN/CPRA and a parallel SA baseline.

tspy

An optimization package for the traveling salesman problem

flowty

Network optimisation solver

pycomposer

pycomposer is Python library for Algorithmic Composition or Automatic Composition based on the stochastic music theory and the Statistical machine learning problems. Especialy, this library provides apprication of the Algorithmic Composer based on Generative Adversarial Networks(GANs) and Conditional Generative Adversarial Networks(Conditional GANs).

jssenv

An OpenAi Gym environment for the Job Shop Scheduling problem.

hallelujah

Compute the Approximate Vertex Cover for undirected graph encoded in DIMACS format.

lp-comp

Python library for coordinated planning in two-level systems, finding compromise solutions between a Center and Elements using mathematical models & a GUI.