A Novel Binary Variable Representation for Genetic and Evolutionary Algorithms - Liang Yong

Based on the theoretical guidance and existing recommendations for designing efficient genetic representations, we investigate a novel genetic representation - a splicing/decomposable (S/D) binary encoding in this paper. The S/D binary representation can be spliced and decomposed to describe potential solutions of the problem with different precisions by different number of uniform-salient building blocks (BBs). According to the characteristics of the S/D binary representation, genetic and evolutionary algorithms (GEAs) can be applied from the high scaled to the low scaled BBs sequentially to avoid genetic drift and improve GEAs' performance. Our theoretical and empirical investigations reveal that the S/D binary representation is more proper than other existing binary encodings for GEAs searching.