Solving the job shop scheduling problems by an immune algorithm

被引：0
|
作者：
Zuo, XQ [1 ]
Fan, YS [1 ]
机构：
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
来源：
PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9 | 2005年
关键词：
job shop scheduling; immune algorithm; optimization computation; evolutionary algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
An immune algorithm is presented for solving the job shop scheduling problem. In the algorithm, the niche technology is used to keep the diversity of the population and chaos variables are employed to perform antibody mutation. The code of an antibody is based on random keys, and a heuristic process is given to decode the antibody into a parameterized active schedule to reduce the solution space. Experimental results demonstrate the algorithm is effective for solving job shop problems.
引用
收藏
页码：3282 / 3287
页数：6
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