Single Vs Hierarchical Population-Based Memetic Algorithm for Sat-Encoded Industrial Problems:A Statistical Comparison

In this work, a hierarchical population-based memetic algorithm for solving the satisfiability problem ispresented. The approach suggests looking at the evolution as a hierarchical process evolving from a coarsepopulation where the basic unit of a gene is composed of cluster of variables that represent the problem toa fine population where each gene represents a single variable. The optimization process is carried out byletting the converged population at a child level serve as the initial population to the parent level. Abenchmark composed of industrial instances is used to compare the effectiveness of the hierarchicalapproach against its single-level counterpart.