Improved clonal selection algorithm based on the directional update strategy

Abstract At present, many cloning selection algorithms have been studied, and improvements made to the cloning, mutation steps. However, there is a lack of research on optimization updating operation The clonal algorithm traditionally updated through random complement antibodies, which blind uncertain process. added antibodies may gather near local optimal solution, resulting in need for more iterations obtain global solution. To solve this problem, our improved introduces crowding degree factor antibody stage determine whether between antibodies. By eliminating with high potential poor affinity, guides update direction solution ensures stable convergence fewer iterations. Experimental results show that overall performance 1% higher than 2.2% genetic algorithm, indicating effective. also transplanted other algorithms, by 0.97%, can be beneficial supplement algorithms.