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

摘要： 经过多年的发展，研究人员设计出大量的免疫算法来解决多目标优化问题。基于三种免疫算子：克隆选择算子、超突变交叉算子和重组存储记忆算子，并通过分析三种算子何时或以何种方式对免疫算法中种群多样性产生影响，从而对免疫算子与种群多样性之间的联系进行了研究。对NNIA和CMOIA两种经典免疫算法在两个基准问题上进行实验分析，实验结果表明克隆选择算子对于算法多样性有消极影响，而超突变交叉算子和重组记忆存储算子则会帮助算法维护多样性。

关键词: 多目标优化免疫算法, 免疫算子, 多样性