Proposal of a Method for Measuring Similarity between Swarm Intelligence Optimziation Methods

Abstract

In this paper, we aim to quantitatively classify the vast number of swarm intelligence optimiza-(breakpoint)tion methods, and propose to express the similarity between two swarm intelligence optimization methods as the quantitative difference between the environments (fitness functions) that make the two solution search processes similar. We also propose a framework for measuring the similarity of methods based on this idea. Furthermore, we use this framework to quantitatively compare the two swarm intelligence opti-(breakpoint)mization methods and quantitatively show the differences between the methods. However, the comparison shows that the similarity is not high between similar methods with slightly different parameter values. The reason for this result is thought to be due to the method for measuring the similarity between the two solution search processes, and we show that improving the method for measuring similarity is a future challenge.