紧凑遗传算法(CGA)具有存储成本低的优点,但是其容易出现早熟。该文提出一种基于变异的紧凑遗传算法(MBCGA)。MBCGA在CGA的基础上,引进变异算子,完整地体现生态进化中的选择、遗传和变异,提高了局部寻优以及算法克服早熟的能力。试验结果表明,MBCGA保留存储成本低的优点,具有较快的收敛速度。变异算子的局部寻优作用明显。 The Compact Genetic Algorithm (CGA) has the advantage of low storage costs, but it is prone to precocity. This paper proposes a mutation based compact genetic algorithm (MBCGA). On the basis of CGA, MBCGA introduces mutation operator, which fully embodies the selection, heredity and mutation in ecological evolution, improves local optimization and the ability of the algorithm to overcome precocious puberty. The experimental results show that MBCGA retains the advantages of low storage cost and fast convergence speed. Local optimization of mutation operator is obvious.