Mining gene structures to inject artificial chromosomes for genetic algorithm in single machine scheduling problems

被引:40
作者
Chang, Pei-Chann [1 ]
Chen, Shih-Shin
Fan, Chin-Yuan
机构
[1] Yuan Ze Univ, Dept Informat Management, Tao Yuan 32026, Taiwan
[2] Yuan Ze Univ, Dept Ind Engn & Management, Tao Yuan 32026, Taiwan
关键词
genetic algorithm; single machine scheduling; total deviation; dominance properties;
D O I
10.1016/j.asoc.2007.06.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a genetic algorithm with injecting artificial chromosomes is developed to solve the single machine scheduling problems. Artificial chromosomes are generated according to a probability matrix which is transformed from the dominance matrix by mining the gene structure of an elite base. A roulette wheel selection method is applied to generate an artificial chromosome by assigning genes onto each position according to the probability matrix. The higher the probability is, the more possible that the job will show up in that particular position. By injecting these artificial chromosomes, the genetic algorithm will speed up the convergence of the evolutionary processes. Intensive experimental results indicate that proposed algorithm is very encouraging and it can improve the solution quality significantly. (C) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:767 / 777
页数:11
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