A Splicing/Decomposable Binary Encoding and Its Novel Operators for Genetic and Evolutionary Algorithms - Liang Yong

Most of the real-world problems could be encoded by different representations, but genetic and evolutionary algorithms (GEAs) may not be able to successfully solve the problems based on their phenotypic representations, unless we use some problem-specific genetic operators. Therefore, a proper genetic representation is necessary when using GEAs on the real-world problems (Goldberg, 1989; Liepins, 1990; Whitley, 2000; Liang, 2011). A large number of theoretical and empirical investigations on genetic representations were made over the last decades. Earlier work (Goldberg, 1989c; Liepins & Vose, 1990) has shown that the behavior and performance of GEAs is strongly influenced by the representation used. As a result many genotypic representations were made for proper GEAs searching. Among of them, the binary, integer, real-valued, messy and tree structure representations are the most important and widely used by many GEAs.