Title
Mining gene structures to inject artificial chromosomes for genetic algorithm in single machine scheduling problems
Abstract
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.
Year
DOI
Venue
2008
10.1016/j.asoc.2007.06.005
Appl. Soft Comput.
Keywords
Field
DocType
gene structure,mining gene structure,particular position,genetic algorithm,dominance matrix,single machine scheduling,probability matrix,proposed algorithm,artificial chromosome,evolutionary process,total deviation,single machine scheduling problem,elite base,dominance properties,assigning gene
Convergence (routing),Single-machine scheduling,Stochastic matrix,Matrix (mathematics),Fitness proportionate selection,Artificial intelligence,Human artificial chromosome,Mathematics,Genetic algorithm,Machine learning,Speedup
Journal
Volume
Issue
ISSN
8
1
Applied Soft Computing Journal
Citations 
PageRank 
References 
24
1.05
21
Authors
3
Name
Order
Citations
PageRank
Pei-Chann Chang11752109.32
Shih-Shin Chen2343.40
Chin-Yuan Fan347328.27