steady state Genetic Algorithm

Initialization [Population]
Evaluation [ Population]
Gen=0
Do
Selected_Parents = Selection[Population]
Created_Offspring= Recombination[selected_parents]
Mutation[Created_Offspring]
Population = Created_Offspring+Replacement[Population]
Evaluation[Created_Offspring]
Gen=Gen+1
Until Stop_Criterion
The main difference between the sGA and ssGA is:
Selection : in this algorithm we can mainly used tournament selection .
Crossover : we can mainly used (2X) or (UX) .
Mutation : we can use high probability for mutation because ssGA can work with high mutation value duo to the Replacement strategies.
Replacement : the main idea in ssGA is the replacement strategy


The simple genetic algorithm replace the oldest population with the new one.
In 1975 , De Jong find the Elitism idea which keep the best individual in the old population in order to prevent damage there chromosome by using Crossover and mutation.
The individual that remain in the old population is named (Generation Gap).