求解随机阻塞批量流水线调度问题的改进人工蜂群算法  

An improved artificial bee colony algorithm for stochastic blocking lot-streaming flow shop scheduling problem

作　　者：韩玉艳[1] 巩敦卫[1] 张勇[1] 

机构地区：[1]中国矿业大学信息与电气工程学院,江苏徐州221116

出　　处：《中国科技论文》2015年第14期1688-1695,1699,共9页China Sciencepaper

基　　金：中国博士后科学基金资助项目(2014T70557;2012M521142);江苏省博士后科研资助计划项目(1301009B);江苏省普通高校研究生科研创新计划资助项目(CXZZ13_0932)

摘　　要：针对含有随机加工时间的阻塞批量流水线调度问题,利用蒙特卡洛采样方法,将不确定加工时间的阻塞批量流水线调度问题转化为确定加工时间的阻塞批量调度问题。采用改进的人工蜂群算法,对上述转化后的调度问题进行求解。算法中加入了和声搜索和基于插入操作的局部搜索算子,以改进全局探索和局部开发能力,并将改进的算法应用到阻塞批量调度的24个算例中。仿真实验结果表明,改进的人工蜂群算法能够降低调度中的不确定因素带来的影响,产生高质量的解。For the blocking lot-streaming flow shop scheduling problem with stochastic processing time,a method is proposed to transform it into a determinate one using Monte Carlo sampling method.An improved artificial bee colony algorithm is developed, in which a harmony search and local search based on insertion operators are adopted to balance the algorithm’s capability in explo-ration and exploitation.The proposed algorithm is applied to 24 instances of blocking lot-streaming flow shop scheduling prob-lem.The experimental results show that the improved algorithm can generate solutions with high quality and reduce the influence resulting from uncertainties.

关 键 词：阻塞批量调度 随机加工时间 蒙特卡洛 人工蜂群 和声搜索算子 

分 类 号：TB497[一般工业技术] TP18[自动化与计算机技术—控制理论与控制工程]