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

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Provided by: Academy & Industry Research Collaboration Center
Topic: Software
Format: PDF
In this paper, a hierarchical population-based memetic algorithm for solving the satisfiability problem is presented. The approach suggests looking at the evolution as a hierarchical process evolving from a coarse population where the basic unit of a gene is composed of cluster of variables that represent the problem to a fine population where each gene represents a single variable. The optimization process is carried out by letting the converged population at a child level serve as the initial population to the parent level. A benchmark composed of industrial instances is used to compare the effectiveness of the hierarchical approach against its single-level counterpart.
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