NichePSO and the Merging Subswarm Problem

The NichePSO algorithm was the first particle swarm optimization algorithm to utilize parallel swarms as an approach to solve multimodal optimization problems. Despite its strong results over many years of research, the NichePSO algorithm has always suffered from a major fundamental issue: The NichePSO algorithm uses multiple smaller subswarms that each search independent sections of the search area, searching for the different optima across the problem landscape. However, each run often ends with a single large subswarm absorbing every other subswarm that has been created, losing track of many of the optima found. This paper analyzes the NichePSO algorithm in detail, and shows evidence that this problem is caused by the subswarm merging strategy being used. Alternative merging approaches are proposed and it is shown that they do not suffer from the same issue as the traditional algorithm.