Naeemeh146/cec-benchmark-2013-python

for testing metaheuristic algorithm which is specific for continuous search spaces like Particle Swarm optimizations, Differential evolutions, etc, one can be sure about the performances of algorithm bt testing them in this benchmark. benchmark has been defined by IEEE World Congress on Computational Intelligence in C++. then developers implemented them in MATLAB and R. Now I have implemented them in Python as these language getting hit between data scientists a lot. I hope you find it useful.

Title: Python Implementation of IEEE CEC 2013 Benchmark for Metaheuristic Algorithms

This repository offers a Python implementation of the IEEE CEC 2013 benchmark, originally defined by the IEEE World Congress on Computational Intelligence. This benchmark is essential for testing the performance of metaheuristic algorithms specifically designed for continuous search spaces, including Particle Swarm Optimization (PSO) and Differential Evolution (DE). While previous implementations exist in C++, MATLAB, and R, this Python version caters to the growing popularity of Python among data scientists.

This project is a valuable resource for researchers and developers looking to evaluate and compare the efficiency of various metaheuristic algorithms in Python.

Keywords: IEEE CEC 2013, Python, Metaheuristic Algorithms, Particle Swarm Optimization, Differential Evolution, Continuous Search Space, Benchmark, Computational Intelligence, Data Science.