The use of explicit building blocks in evolutionary computation

This paper proposes a new algorithm to identify and compose building blocks. Building blocks are interpreted as common subsequences between good individuals. The proposed algorithm can extract building blocks from a population explicitly. Explicit building blocks are identified from shared alleles among multiple chromosomes. These building blocks are stored in an archive. They are recombined to generate offspring. The additively decomposable problems and hierarchical decomposable problems are used to validate the algorithm. The results are compared with the Bayesian Optimization Algorithm, the Hierarchical Bayesian Optimization Algorithm, and the Chi-square Matrix. This proposed algorithm is simple, effective, and fast. The experimental results confirm that building block identification is an important process that guides the recombination procedure to improve the solutions. In addition, the method efficiently solves hard problems.