摘要
针对柔性作业车间调度问题提出两种新颖的邻域搜索方法:极值优化邻域和扩展的关键块邻域,并将其结合形成搜索范围广、寻优能力强的复合邻域;以复合邻域为基础,构造改进的遗传算法,使之兼具广阔的全局搜索能力和深刻的局部搜索能力。另外,算法采用较新颖的两级编码方式,使得对于工序排序编码和机器分配编码两部分可采用相同或相近的遗传算子进行运算,提高运算效率。对算例的测试结果及与其他算法的比较验证了本文算法的有效性。
Two neighborhood searching methods for flexible job-shop scheduling problems are proposed,one is extremal optimal neighborhood searching and the other is extended critical block neighborhood searching.These two methods are combined to form a neighborhood searching operator named ECE operator,holding both wide searching space and strong searching ability.An improved genetic algorithm is constructed employing the ECE operator to enhance its local search ability.Besides,a novel coding mode of the algorithm is proposed to create two-part chromosomes： operations permutation code and machines assignment code;the coding method enables both parts of the chromosomes being manipulated by the same genetic operators,which simplifies the algorithm＇s structure.The computation results validate the effectiveness of the proposed algorithm.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2010年第8期1662-1666,共5页
Systems Engineering and Electronics
基金
广东省自然科学基金(8452902001001552)资助课题
关键词
柔性作业车间调度
极值优化
扩展关键块
遗传算法
flexible job-shop scheduling
extremal optimization
extended critical block
genetic algorithm
