A Novel DOE-Based Selection Operator for NSGA-II Algorithm

In the present paper, a modified variant of Non-dominated Sorting Genetic Algorithm (NSGA-II) is introduced. The proposed algorithm uses Design of Experiments (DOE) regression model to insert ideal points to the population in each generation. The performance of the proposed algorithm is investigated on five bi-objective benchmark problems and the results are compared with classic NSGA-II. The empirical comparison of the results show the efficiency of the Modified NSGA-II in finding non-dominated points much faster and often better than the classic version.

کلیدواژه ها:

Design of Experiments ، Regression model ، Non-dominated sorting genetic algorithm (NSGA-II) ، Selection Operator