An evolutionary algorithm based on decomposition for multimodal optimization problems

Abstract

This paper presents a non-parameter method to identify the peaks of the multi-modal optimization problems provided that 
the peaks are characterized by a smaller objective values than their neighbors and by a relatively large distance from 
points with smaller objective value. Using the identified peaks as the seeds, we decompose the population into some 
subpopulations and dynamically allocate the computational effort to different subpopulations. We evaluate the proposed 
approach on the CEC2015 single objective multi-niche optimization problems. The promising experimental results show its 
efficacy.