量子进化算法和免疫算法都是解决优化问题的强有力算法。在分析了量子进化算法搜索的特点和免疫算法的机理基础上，对它们进行比较，阐明了二者的不同特点-Quantum-inspired evolutionary algorithms and immune algorithms are a powerful algorithm to solve optimization problems. After analyzing the characteristics of the quantum evoluti

分析量子进化算法和免疫算子的特点,提出一种分级变异的量子进化算法,用于求解多目标优化问题-Analysis of quantum-inspired evolutionary algorithms and immune operator characteristics, presents a hierarchical variation of the quantum-inspired evolutionary algorithm for solving multi-objective optimi