基于递阶遗传算法的并行多机调度优化

针对最小化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，采用一种递阶编码方案，此编码与调度方案一一对应。用递阶遗传算法优化并行多机调度不需设计专门的遗传算子，操作简单。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。

Optimization for parallel multi-machine scheduling based on hierarchical genetic algorithm

With regard to the identical and non-identical parallel machine scheduling for minimizing the makespan, a hierarchical genetic algorithm was proposed. Its coding method is simple and can effectively reflect the scheduling policy, and the methods of crossover and mutation need no special design. The computational results suggest that the hierarchical genetic algorithm is efficient and fit for large-scale identical and non-identical parallel machine scheduling.