基于递阶遗传算法的最小加权完工时间并行机调度

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.

Hierarchical Genetic Algorithm-Based Parallel Machine Scheduling for Minimization of Total Weighted Completion Time

In order to solve a kind of identical and non-identical parallel machine scheduling problem for minimizing the total weighted completion time,a hierarchical genetic algorithm was proposed. Its coding method was simple and could effectively reflect the scheduling policy. The computational results suggest that the hierarchical genetic algorithm is efficient and applicable to large-scale parallel identical and non-identical machine scheduling problems. A comparison with Cheng's genetic algorithms was made with the proposed algorithm having simpler operation and faster convergence.