A research toolkit for particle swarm optimization in Python

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

🎯 A comprehensive gradient-free optimization framework written in Python

A framework for single/multi-objective optimization with metaheuristics

PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants. https://pypop.rtfd.io/

Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.

A MSc's Dissertation Project which focuses on Vehicle Routing Problem with Time Windows (VRPTW), using both exact method and heuristic approach (General Variable Neighbourhood Search)

Artificial Bee Colony Algorithm in Python.

Different meta-heuristic optimization techniques for feature selection

This toolbox offers advanced feature selection tools. Several modifications, variants, enhancements, or improvements of algorithms such as GWO, FPA, SCA, PSO and SSA are provided.

An implementation of various metaheuristics adapted to train neural networks

MetaGen: A framework for metaheuristic development and hyperparameter optimization in machine and deep learning

Travelling salesman problem with 3opt move and 2opt perturbation

Metaheuristic(Genetic algorithm, Particle swarm optimization, Cuckoo search, Grey wolf optimizer), Reinforcement Learning with Python

A python Framework for Simple Ant Colony Optimization Algorithms

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.

🎓An AI tool to assist universities with optimal allocation of students to supervisors for their dissertations. Devised a multi-objective genetic algorithm for the task.

Customising optimisation metaheuristics via hyper-heuristic search (CUSTOMHyS). This framework provides tools for solving, but not limited to, continuous optimisation problems using a hyper-heuristic approach for customising metaheuristics. Such an approach is powered by a strategy based on Simulated Annealing. Also, several search operators ser…

Metaheuristic approach for solving pick up and delivery problem with time windows.

Solving Multiple Sequence Alignment (MSA) problems with multi-objective metaheuristics