Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.

🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.

A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

Derivative-Free Global Optimization Method (C++, Python binding)

[NeurIPS 2023] DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

A Python implementation of the Ant Colony Optimization Meta-Heuristic

Matlab Module for Stock Market Prediction using Simple NN

An Ant Colony Optimization algorithm for the Traveling Salesman Problem

A Hyper-Heuristic framework

Modular Java framework for meta-heuristic optimization

Exact and meta-heuristic algorithms for NP problems

Meta-heuristic algorithm for Multi-Trip Vehicle Routing Problem with Time Windows

In this section, I share the Meta-Heuristic algorithm codes that I wrote myself

Black Widow Optimization implemented in pure Python.

📄 Official implementation regarding the paper "Creating Classifier Ensembles through Meta-heuristic Algorithms for Aerial Scene Classification".

Fast and easy solver for a lot of Vehicle Routing constraints

🐝 Nature-Inspired Optimization Applied to Deep Learning for ICMC/USP mini-course.

Online selection hyper-heuristic with generic parameter control in low-level heuristics (meta-heuristic).

Currently a prototype implementation of Pareto local search algorithm in preparation for an upcoming project

It was developed by creating a hybrid structure with the techniques of K-nearest neighbor algorithm and metaheuristic search algorithms. SOS Algorithm was used as the Meta-Heuristic algorithm.