Description of the Micro Genetic Algorithm Program

The micro-genetic algorithm program used in this study is generation-based (that is, children replace the parents each generation except for those parents selected by elitism), uses binary encoding with a tournament selection for choosing the parents for the next generation and uniform crossover. Other operators such as jump and creep mutation and niching were not used, following the results in (). Table  summarizes the parameters of the micro-genetic algorithm.

 

Population size 5 Crossover rate 0.95

Mutation rate 0.0 Creep mutation rate 0.0

Minimum model parameter value 2200 Maximum model parameter value 3200

Elitism Yes Niching No

Selection strategy Tournament Number of children 1