Hybrid Intelligent Algorithm Solving Uncertainty Job-Shop Scheduling Problem

被引:0
作者
Hu, Yang-Jun [1 ]
Song, Cun-li [1 ]
机构
[1] Sch Dalian Jiao Tong Univ, Dalian 116052, Peoples R China
来源
PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN MECHANICAL ENGINEERING AND INDUSTRIAL INFORMATICS (AMEII 2016) | 2016年 / 73卷
关键词
Job shop scheduling; fuzzy mathematics; immune; taboo;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Researched the uncertain Job-Shop Scheduling, on the basis of the original triangular fuzzy number to describe fuzzy processing time, structured the fuzzy Job-Shop Scheduling model. Algorithm using the concept of "big valley" topology represent solution space, using strong swap mutations in early immune genetic algorithm, and implanting vaccines in three styles, rapidly improved the ability of search "mountain"; After immune selection using taboo search's "climb" idea improve the local search ability of the algorithm, so as to choose the individual with maximum satisfaction in the "big valley" quickly and efficiently. And through Matlab2012a software simulation examples verify the effectiveness of the immune genetic and taboo hybrid intelligent algorithm.
引用
收藏
页码:528 / 534
页数:7
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