BeeOptimal

EvoloPy toolbox provides classical and recent nature-inspired metaheuristic for the global optimization.

A repository with a data set including instances and results from literature for the Job Shop Scheduling Problem (JSSP). While the raw data is provided as text files, it is also compiled in an R package with an API around it.

Python automated machine learning framework.

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

Feature Selection for Credit Scoring using Genetic Algorithm Wrapper(Information Gain)

Artificial Bee Colony for generic feature tuning

Firefly Algorithm (FA) Image Segmentation Using Clustering

Multilevel thresholding segmentation method

Visit: https://aliasgharheidari.com/HGS.html. HGS optimizer is a population-based method with stochastic switching elements that enrich its main exploratory and exploitative behaviors and flexibility of HGS in dealing with challenging problem landscapes. The algorithm has been compared to LSHADE, SPS_L_SHADE_EIG, LSHADE_cnEpSi, SHADE, SADE, MPEDE, and JDE methods.

PSO + SA Image Segmentation