Hi my dear Susanne
Your question is very common. Anyone who asks me this question, I have the best answer for her/him.NO,There is no formula for calculating Population size.However, there are several tricks in optimization problems for number of crossover,number of mutation and population size.for instance,Some optimization experts believe that choosing 4 to 6 times the number of decision variables is Appropriate for Population size.But In my opinion,based on my experience,the number of Population size, Mutation, generations and crossover selections for both single and multi-objective functions are completely random. Basically, they will depend on the type of your optimization problem. For example, for an optimization problem case(A),it may be optimized perfect just with Population size( = 10) , Mutation(=0.05) ,generations(=10) and crossover(=0.7) ,while for another optimization problem case(B), it may be optimized perfect with Population size( = 200) , Mutation(=0.2) ,generations(=100) and crossover(=0.6). The most important point is that you have to run your optimization problem for different selections and find the best selection .it is very common.
Based on my experience in the optimization, Choosing among Population size( = 20 to 50) , Mutation(=0.05 to 0.2) ,generations(=10 to 100) and crossover(=0.55 to 0.8) work very well.
If you still have any questions about optimization, I am very happy to ask me your questions.
Cheers
Navid Delgarm
Your question is very common. Anyone who asks me this question, I have the best answer for her/him.NO,There is no formula for calculating Population size.However, there are several tricks in optimization problems for number of crossover,number of mutation and population size.for instance,Some optimization experts believe that choosing 4 to 6 times the number of decision variables is Appropriate for Population size.But In my opinion,based on my experience,the number of Population size, Mutation, generations and crossover selections for both single and multi-objective functions are completely random. Basically, they will depend on the type of your optimization problem. For example, for an optimization problem case(A),it may be optimized perfect just with Population size( = 10) , Mutation(=0.05) ,generations(=10) and crossover(=0.7) ,while for another optimization problem case(B), it may be optimized perfect with Population size( = 200) , Mutation(=0.2) ,generations(=100) and crossover(=0.6). The most important point is that you have to run your optimization problem for different selections and find the best selection .it is very common.
Based on my experience in the optimization, Choosing among Population size( = 20 to 50) , Mutation(=0.05 to 0.2) ,generations(=10 to 100) and crossover(=0.55 to 0.8) work very well.
If you still have any questions about optimization, I am very happy to ask me your questions.
Cheers
Navid Delgarm
