Comparative Analysis of Ant Colony and Particle Swarm Optimization Algorithms for Distance Optimization
Arushi Gupta, Smriti Srivastava · Procedia Computer Science · 2020
In this paper, we have solved one of the widely popular problems in the domain of control systems – distance optimization using two separate swarm intelligence algorithms – particle swarm and ant colony optimization. The problem is successfully solved with both algorithms and subsequently quantitative comparison between their performances is done. Simulated results show the more recently developed ant colony optimization algorithm to be better and more robust of the two. The requisite simulations are carried out and results are obtained in the MATLAB environment.