EvoloPy Demo: An open source nature-inspired optimization toolbox for global optimization in Python

As an initiative to keep an implementation of the recent nature-inspired metaheuristics as well as the classical ones in a single open source framework, we introduce EvoloPy. EvoloPy is an open source and cross-platform Python framework that implements a wide range of classical and recent metaheuristic algorithms. The goal of the framework is to take advantage of the rapidly growing scientific community of Python and provide a set of robust optimizers as free and open source software. We believe that implementing such algorithms in Python will increase their popularity and portability among researchers and non-specialists coming from different domains. The powerful libraries and packages available in Python (such as NumPy) will make it more feasible to apply metaheuristic algorithms for solving complex problems on a much higher scale. EvoloPy facilitates designing new algorithms or improving, hybridizing, and analyzing the current ones. Github: https://github.com/7ossam81/EvoloPy Google colab: https://github.com/7ossam81/EvoloPy/blob/master/EvoloPy.ipynb Paper: https://www.scitepress.org/Papers/2016/60482/60482.pdf