Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
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Updated
Jan 23, 2025 - Python
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 Algorithm (C++, Python binding) - Continuous, Discrete, TSP, NLS, MINLP
[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
Heuristic Optimization for Python
Tuning the Parameters of Heuristic Optimizers (Meta-Optimization / Hyper-Parameter Optimization)
A Hyper-Heuristic framework
An Ant Colony Optimization algorithm for the Traveling Salesman Problem
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.
Archive of my older research papers on optimization
📄 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
Online selection hyper-heuristic with generic parameter control in low-level heuristics (meta-heuristic).
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