Abstract: The clonal selection algorithm is an evolutionary optimization algorithm on the basis of clonal selection theory of the immune system, but it is subject to antibody concentration, leading less stableness. Based on the traditional clonal selection algorithm and consideration of the antibody concentration and diversity of the population, we proposed a novel clonal feedback optimization algorithm. The proposed algorithm is integrated into an evolution feedback depth model and population survivability idea, to effectively improve the stability of the algorithm. Finally, the proposed algorithm is applied to the task scheduling in grid computing,and achieves satisfactory results.

Key words: Immune system, Clonal selection algorithm, Feedback mechanism, Clonal feedback optimization algorithm,Grid computing