An easy and convienent way to performance test python code.

A collection of Benchmark functions for numerical optimization problems

Single- and Multi-Objective Optimization Test Functions

Collection of Multi-Fidelity benchmark functions

A Fortran 95 code for Particle Swarm Optimization. The code is general. The fitness function is defined in a separate file and can be replaced by any user defined fitness function.

A collection of the most commonly used Optimisation Algorithms for Data Science & Machine Learning

A set of common benchmark functions for testing optimization algorithms in Julia

This repository is used to implement and analyze nature inspired computing algorithms on various benchmark function. We also try to solve some real world problems by MHA.

This repository contains the standard Particle Swarm Optimization code (Matlab M-file) for optimizing the benchmark function.

Javascript implementations of some of the main metaheuristic algorithms for bound constraint single objective continuous optimization problems.

A study on swarm intelligence optimizing neural networks for workload elasticity prediction

**optiGTest** is a MATLAB's toolbox which regroups many existing test functions used for studying the performance of approximation techniques and optimization strategy. In particular, gradient of the test functions are provided.

A pure-MATLAB library of EVolutionary (population-based) OPTimization for Large-Scale black-box continuous Optimization (evopt-lso).

This repository contains the Harris Hawks Optimization code (matlab M-file) for optimizing the benchmark function.

Optimization environment for TimeNET

Benchmark functions to test optimisation algorithms.

Benchmark functions for validating optimization algorithm in C++

A set of Jupyter notebooks that investigate and compare the performance of several numerical optimization techniques, both unconstrained (univariate search, Powell's method and Gradient Descent (fixed step and optimal step)) and constrained (Exterior Penalty method).

An efficient, modular and multicore-aware framework for Particle Swarm Optimization

A MATLAB toolkit of benchmark functions for numerical experiments of optimization.