摘要
针对有限缓冲区批量流水车间分批调度问题,综合考虑提前惩罚和延期惩罚为目标建立模型并改进标准布谷鸟算法求解。为了提升布谷鸟算法的搜索效率,将固有的淘汰概率改为动态自适应产生的概率。另外引入基于关键路径的局部搜索作为一种优化机制,用来寻求种群的更优解。通过仿真实验所得结果与标准布谷鸟算法比较,证明了改进布谷鸟算法具有更好的稳定解和更高的寻优能力。
Aiming at the blocking lot-streaming flow shop scheduling problem under actual working conditions,the cuckoo search algorithm was developed to improve the early evaluation and postponement evaluation.The dynamic adaptive mechanism and the local search based on the critical path were adopted to improve the capability of the exploitation of the proposed algorithm.The improved cuckoo search algorithm was applied to solve the problem by searching a optimal path based on consistent sub-lots mode.By comparing the simulation results based on proposed algorithm with the results from the standard cuckoo search algorithm,it is proved that the proposed cuckoo algorithm in this paper possesses better solution stability and higher precision.
作者
彭菁
段程
李益兵
PENG Jing;Duan Cheng;Li Yibing(School of Mechanical and Electronic Engineering,Wuhan University of Technology,Wuhan 430070,China)
关键词
布谷鸟搜索算法
动态自适应
关键路径
非等量分批
cuckoo search algorithm
dynamic adaptive mechanism
critical path
consistent sub-lots
