Gaussian Artificial Bee Colony Algorithm Approach Applied to Loney's Solenoid Benchmark Problem

Optimization metaheuristics, such as Particle Swarm Optimization, Ant Colony Optimization and bacterial foraging strategies have become very popular in the optimization community and have been successfully applied to electromagnetic device design. The Artificial Bee Colony (ABC) algorithm is a rather new bio-inspired swarm intelligence approach which is competitive with other population-based algorithms and has the advantage of using fewer control parameters. In this work, a standard and an improved version of the ABC algorithm using Gaussian distribution are applied to Loney's solenoid problem, showing the suitability of these methods for electromagnetic optimization.