ACOR Algorithm’s Efficiency for Electromagnetic Optimization Benchmark Problems

This article studies the efficiency of an Ant Colony Optimization (ACO) algorithm for the solving of electromagnetic optimization problems. A modified version of the ACO for continuous optimization, namely ACO
R
, is used to solve two benchmark electromagnetic problems referring to the optimization of coils configuration. After choosing the appropriate size of the population of ants, the ACO
R
algorithm performances are compared with results obtained with other evolutionary computation strategies such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). For one problem ACO
R
outperforms the variants of the GA and PSO used at all statistical criteria checked, whereas for the other problem ACO
R
is ranked as the second best after the PSO based algorithm tested.