Comparison of PSO and ABC: From A Viewpoint of Learning

Abstract

The learning mechanisms in Partial Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithm are studied. Four basic learning elements are considered, including learning subject, learning object, learning result and learning rules. Both PSO and ABC generate new solutions by learning to explore/exploit promising subspace. For the solution generation operators in each algorithm, we study the learning mechanism and analyze their exploration and exploitation ability. This study gives more insights on the similarity and differences between PSO and ABC.