Improved Clonal Selection Algorithm (ICLONALG)

Abstract

Natural immune system uses clonal selection algorithm to define the basic features of an immune response to an antigenic stimulus. It establishes the idea that only those cells that recognize the antigens are selected to proliferate. The selected cells are subjected to an affinity maturation process, which improves their affinity to the selective antigen. In this paper, we propose a computational implementation of the clonal selection principle that explicitly takes into account the affinity maturation of the immune response. The general algorithm, named CLONALG, is primarily derived to solve optimization problems, emphasizing multimodal and combinatorial optimization. In this paper there is some modification in the selection and reproduction process to maximize the optimized result.