Multi-population genetic algorithm with Hierarchical execution
Tzung‐Pei Hong, Yuan-Ching Peng, Wen-Yang Lin · 2016
In this paper, we design a hierarchical execution architecture of genetic algorithms (GAs). We present a variant of genetic algorithms known as Hierarchical GA (HGA) based on the proposed architecture. In HGA, the population is divided into several sub-populations, which are initially placed at the lowest level. When the GA process at the level terminates, the GA process goes up to the next level. Experiments are conducted to verify the performance of the proposed mechanism.