Inspired from the immune memory mechanism in immune systems, a clonal selection algorithm based on
mutation memory matrix, CSAB3M, is proposed in order to optimize complex functions. Firstly, an immune memorial
matrix is developed to save mutation information, which guides operations of clone and mutation of antibodies, so that the
local search ability can be improved. Then, new antibodies resulted from the comprehensive information of contemporary
population are generated and introduced to the population in order to improve global search ability. Finally, the optimal
antibody does self-learning operator to improve the precision of the algorithm. Simulation results on standard test functions
show that the algorithm is well suitable for the complex function optimization, and has the characteristics of rapid
convergence, powerful global search capability, high precision and good robustness.