General Genetic Algorithm Let g=0 (2) Initialize the initial generation Cg While no stopping criterion is satisfied (a)Evaluate the fitness of each individual in Cg (b)g<g+1. c)Select parents from Ca-1 (d) Recombine selected parents through cross-over to form offspring oa with a probability p) (e)Mutate offspring in Oa with a probability pm) (f select the new generation Ca from (the previous generation Ca-1, e.g the best individuals are copied and the offspring g g: generation Note: The things in 0 might or might not be carried out 2021/1/30 EIE426-AICV2021/1/30 EIE426-AICV 10 General Genetic Algorithm (1) Let g = 0. (2) Initialize the initial generation Cg . (3) While no stopping criterion is satisfied (a) Evaluate the fitness of each individual in Cg . (b) g  g+1. (c) Select parents from Cg-1 . (d) Recombine selected parents through cross-over to form offspring Og (with a probability pc ). (e) Mutate offspring in Og (with a probability pm). (f) Select the new generation Cg from (the previous generation Cg-1 , e.g., the best individuals are copied) and the offspring Og . g: generation Note: The things in () might or might not be carried out