关键词: 多目标优化免疫算法, 免疫算子, 多样性

Abstract: After years of development, the researchers design a large number of immune algorithms to solve the multi-objective optimization problem. It is heavily based on three immune operators： the clone selection operator, the hyper-mutation crossover operator, the recombination and memory operator. Then, it analyzes three kinds of operators how or when impact on the diversity of the population immune algorithm, which can show that the immune operator has the link between the diversity of the population. Motivated experimental analysis of NNIA and CMOIA two classic immune algorithms in two reference index values indicates that the clone selection operator with a negative impact on the algorithm diversity, but the hyper-mutation crossover operator or the recombination and memory operator child will help the algorithm to maintain diversity.

Key words: multi-objective optimization immune algorithm, immune operator, diversity