Clonal selection based memetic algorithm for job shop scheduling problems

被引：47
作者：
Yang, Jin-hui [1 ]
Sun, Liang [1 ]
Lee, Heow Pueh [2 ,3 ]
Qian, Yun [4 ]
Liang, Yan-chun [1 ]
机构：
[1] Jilin Univ, Coll Comp Sci & Technol, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China
[2] Inst High Performance Comp, Singapore 117528, Singapore
[3] Natl Univ Singapore, Dept Mech Engn, Singapore 117576, Singapore
[4] Beihua Univ, Inst Elect & Informat Engn, Jilin 132021, Peoples R China
来源：
JOURNAL OF BIONIC ENGINEERING | 2008年 / 5卷 / 02期
基金：
中国国家自然科学基金;
关键词：
job shop scheduling problem; clonal selection algorithm; simulated annealing; global search; local search;
D O I：
10.1016/S1672-6529(08)60014-1
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper. In the proposed algorithm, the clonal selection and the local search mechanism are designed to enhance exploration and exploitation. In the clonal selection mechanism, clonal selection, hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration. In the local search mechanism, a simulated annealing local search algorithm based on Nowicki and Smutnicki's neighborhood is presented to exploit local optima. The proposed algorithm is examined using some well-known benchmark problems. Numerical results validate the effectiveness of the proposed algorithm.
引用
收藏
页码：111 / 119
页数：9
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