Intuitionistic fuzzy logic based quality assessment of simple genetic algorithm

Intuitionistic fuzzy logic has been implemented aiming to derive intuitionistic fuzzy estimations of S. cerevisiae fed-batch cultivation model parameters obtained using standard simple genetic algorithm. Performances of the examined algorithm have been tested before and after the application of the procedure for purposeful model parameters genesis and for three different values of the most sensitive toward convergence time genetic algorithms parameter namely generation gap. Results obtained after the implementation of intuitionistic fuzzy logic for the algorithm performance assessment have been compared and a value of GGAP ensuring the fastest and the most reliable solution has been recommended.