Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
-
Updated
May 31, 2024 - Python
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
Matlab Module for Stock Market Prediction using Simple NN
A Python implementation of the Ant Colony Optimization Meta-Heuristic
[NeurIPS 2023] DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization
Modular Java framework for meta-heuristic optimization
A Hyper-Heuristic framework
An Ant Colony Optimization algorithm for the Traveling Salesman Problem
Derivative-Free Global Optimization Method (C++, Python binding)
Meta-heuristic algorithm for Multi-Trip Vehicle Routing Problem with Time Windows
Local searches for continuous optimization implemented in C#
Fast and easy solver for a lot of Vehicle Routing constraints
Exact and meta-heuristic algorithms for NP problems
📄 Official implementation regarding the paper "Creating Classifier Ensembles through Meta-heuristic Algorithms for Aerial Scene Classification".
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.
Local Search Scheduling with Simulated Annealing
Black Widow Optimization implemented in pure Python.
Social mimic optimization algorithm and engineering applications (SMO algorithm)
Add a description, image, and links to the meta-heuristic topic page so that developers can more easily learn about it.
To associate your repository with the meta-heuristic topic, visit your repo's landing page and select "manage topics."