A Manufacturing Grid Resource Scheduling Model and Its Solution Method with Cloud Adaptive Genetic Algorithm (CAGA)

2012 ◽  
Vol 6 (1) ◽  
pp. 526-529
Author(s):  
Fuqing Zhao ◽  
Jizhe Wang ◽  
Jianxin Tang ◽  
Gang Liu
2009 ◽  
Vol 29 (5) ◽  
pp. 1321-1323
Author(s):  
Jun YAO ◽  
Ting-nian HE ◽  
Yong LI ◽  
Wei-li QU ◽  
Man-fu MA

2011 ◽  
Vol 204-210 ◽  
pp. 1594-1598
Author(s):  
Sheng Jun Xue ◽  
Wei Qi

Traditional resource scheduling algorithm, in grid environment, exist some defects, for example it can not well meet the quality requirements and can not get the optimal solution. This article gives a new resource scheduling method based on improved genetic algorithm. It achieves grid resource scheduling by using real number encoding and activities point crossover. Experiments show that genetic algorithm can reduce executing time and task completion time, and further improve the scalability of resource scheduling model. This algorithm has stability and high efficiency in grid environment.


2009 ◽  
Vol 29 (10) ◽  
pp. 2635-2637
Author(s):  
Ke-jun BI ◽  
Fu-hai DUAN ◽  
Man-fu MA

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