Abstract
Genetic Algorithm consisted of three genetic operators, 〜reproduction, crossover and mutation〜, is called simple GA Simple GA may be applied to many optimization problem which includes discrete variables or/and functions, but sometimes it does not work well. This paper explains the several innovations that were proposed to improve the reliability and efficiency of simple GA. They are growth operator for combinatorial problem, column remedy of missing bits for also combinatorial problem, big mutation for both of combinatorial and scheduling problem, coding method for the problem that includes both of the combinatorial and the scheduling problem, and also coding method for the scheduling problem in which the preceding operations are included.
