Fitness Dependent Optimizer

Fitness Dependent Optimizer (FDO) is a novel swarm intelligence algorithm inspired by bee colony behavior, aiming to efficiently solve optimization problems by dynamically weighting exploration and exploitation phases based on fitness values. Current research focuses on improving FDO's performance, particularly by addressing limitations related to the number of search agents and enhancing its convergence speed, often through modifications like incorporating quasi-random initialization or adapting parameters for specific applications. FDO's demonstrated success in diverse fields, including fault detection in steel plates, COVID-19 diagnosis, and economic load dispatch, highlights its potential as a robust and versatile optimization tool across various engineering and scientific domains.