Empirical comparison of level-wise hierarchical multi-population genetic algorithm
Tzung‐Pei Hong, Yuan-Ching Peng, Wen-Yang Lin, Shyue-Liang Wang · Journal of Information and Telecommunication · 2017
Metaheuristics have recently been commonly used to solve complex problems in real applications. Some scholars used multiple populations in metaheuristic approaches to shorten the execution time in finding nearly optimal solutions. In this paper, we revisit the properties of sub-population execution for genetic algorithm (GA) and design a level-wise hierarchical sub-population architecture. We also make experiments for comparing the performance of the architecture for unimodal and multimodal functions. The experimental results show that using the hierarchical GA architecture produces a more significant improvement on multimodal functions than on unimodal ones.