摘要
针对流水车间调度完工时间最小化问题,对基于流水车间调度问题的混合量子遗传算法提出新的编码方法,对量子进化提出了动态旋转角进化策略。通过对大量的基准问题的仿真实验表明,新算法在优化速度及优化效果上都有了显著的提高。
This paper considers the problem of minimizing the makespan for flow-shop scheduling. An encoding method is proposed for the hybrid quantum evolutionary algorithm, and a dynamic rotation angle strategy is introduced for quantum evolutionary. It is shown from the simulation results that the proposed method can obtain quicker speed and better effectiveness of optimization.
出处
《华东理工大学学报（自然科学版）》
CAS
CSCD
北大核心
2013年第2期189-194,共6页
Journal of East China University of Science and Technology
基金
国家自然科学基金(61174040)
关键词
流水车间调度
量子进化
编码方法
旋转角
flow shop scheduling problem
quantum evolutionary
encoding method
rotation angle
