A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)

Python microframework for building nature-inspired algorithms. Official docs: https://niapy.org

Sample Code Collection of Nature-Inspired Computational Methods

Python automated machine learning framework.

Nature-inspired algorithms for hyper-parameter tuning of Scikit-Learn models.

Nature Inspired Optimization Algorithms

A new metaheuristic for global optimization problems proposed in the IEEE Congress on Evolutionary Computation (CEC), 2018

IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine

(Code) A new workload prediction model using extreme learning machine and enhanced tug of war optimization

Meta-Heuristic Algorithm for Travelling Salesman Problem

SPGD: Search Party Gradient Descent algorithm, a Simple Gradient-Based Parallel Algorithm for Bound-Constrained Optimization. Link: https://www.mdpi.com/2227-7390/10/5/800

The ripple-spreading algorithm for the shortest path problem.

A Python Toolkit for Data Preprocessing with Evolutionary and Nature-Inspired Algorithms.

reflame: Revolutionizing Functional Link Neural Network by Metaheuristic Optimization

A document-level information extraction pipeline for layered cathode materials for sodium-ion batteries.

EvoRBF: A Nature-inspired Algorithmic Framework for Evolving Radial Basis Function Networks

MetaSklearn: A Metaheuristic-Powered Hyperparameter Optimization Framework for Scikit-Learn Models.

The repository containing more advanced examples of usage of NiaPy micro-framework.

GrafoRVFL: A Gradient-Free Optimization Framework for Boosting Random Vector Functional Link Network