Simulated Annealing Python Packages

openjij

OpenJij : Framework for the Ising model and QUBO.

jij-cimod

C++ library for a binary quadratic model

gradient-free-optimizers

Lightweight optimization with local, global, population-based and sequential techniques across mixed search spaces

moptipy

Implementation of metaheuristic optimization methods in Python for scientific, industrial, and educational scenarios. Experiments can be executed in parallel or in a distributed fashion. Experimental results can be evaluated in various ways, including diagrams, tables, and export to Excel.

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.

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.

sko

Swarm Intelligence in Python

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.

tsp-framework

Framework de algoritmos para resolver el Problema del Vendedor Viajero

optapy

OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.

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.

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.

rig-c-sa

Python C module for the Rig simulated annealing placer C kernel

pygan

pygan is Python library to implement Generative Adversarial Networks(GANs), Conditional GANs, Adversarial Auto-Encoders(AAEs), and Energy-based Generative Adversarial Network(EBGAN).

invest-ucm-calibration

Automated calibration of the InVEST urban cooling model with simulated annealing

data-morph-ai

Morph an input dataset of 2D points into select shapes, while preserving the summary statistics to a given number of decimal points through simulated annealing. It is intended to be used as a teaching tool to illustrate the importance of data visualization.

simplestsimulatedannealing

Flexible implementation of Simulated Annealing algorithm for function minimization

pycomposer

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.

rectangle-packing-solver

A solver to find a solution of the 2D rectangle packing problem by simulated annealing (SA) optimization.

phase-slip-sampler

An entropic perturbation sampler for LLMs using orthonormal vector rotation and logit anchoring.

pyamosa

Python implementation of the Archived Multi-Objective Simulated Annealing (AMOSA) optimization heuristic

turingbot

Python interface for TuringBot, a symbolic regression software that discovers mathematical formulas from data

optimizationalgo

Optimization algorithms for the traveling salesman problem