Hidden Genes Genetic Algorithms
Ossama O. Abdelkhalik · 2020
This chapter introduces the concept of Hidden Genes in genetic algorithms that enables genetic algorithms (GAs) to handle Variable-Size Design Space (VSDS) optimization problems. It introduces the biologically inspired concept of hidden genes to address this type of VSDS optimization problems. In the hidden genes concept, all chromosomes in the population are allocated a fixed length equal. It can be concluded that the standard genetic algorithm expectation for the increase in the number of members of a schema due to the combined effect of reproduction, crossover, and mutation is a conservative lower bound in the case of using hidden genes. Optimization problems may be classified based on the existence of constraints, the nature of the design variables, and the nature of the equations involved. Local optimization methods find a local minimum given an initial guess in its neighborhood. Standard GAs are search techniques based on the mechanics of natural selection and genetics.