针对最小化加权完工时间的等同和非等同并行多机调度一类问题,提出了一种递阶遗传算法。该算法根据问题的特点,采用一种染色体递阶编码方案,此编码与调度方案一一对应。计算结果表明,递阶遗传算法是有效的,能适用于大规模等同和非等同并行多机调度问题,通过与Cheng所作编码的遗传算法比较,用递阶遗传算法优化并行机调度操作简单并且收敛速度快。 Aiming at the problems of equal and non-identical parallel multi-machine scheduling with minimized weighted completion time, a hierarchical genetic algorithm is proposed. According to the characteristics of the problem, the algorithm uses a hierarchical coding scheme of chromosomes, which corresponds to the scheduling scheme. The results show that Hierarchical Genetic Algorithm is effective and can be applied to large-scale equivalent and non-equivalent parallel multi-machine scheduling. By comparing with Cheng’s genetic algorithm, Hierarchical Genetic Algorithm (GA) optimizes the scheduling of parallel machines and simplifies the convergence high speed.