DocumentCode :
496240
Title :
A Grid Algorithm for Injection Gate Location Optimization Based on MDG
Author :
Zhendong, Cui ; Xicheng, Wang ; Jianke, Zhang ; Shenming, Gu
Author_Institution :
Dept. of Comput., Zhejiang Ocean Univ., Zhoushan, China
Volume :
1
fYear :
2009
fDate :
24-26 April 2009
Firstpage :
28
Lastpage :
32
Abstract :
The injection mold optimization problems always require huge computer resources, so the grid is a good choice for solving these problems. But for the heterogeneous, distributed and dynamic characters of the grid resources, it is difficult to finish the complex problems efficiently in collaborative way by grid. Based on the Globus Toolkits 4, a four-layer Mold Design Grid (MDG) platform was constructed to meet resource sharing for the complex injection mold optimization. By using multi-population genetic strategy and information-entropy based searching technique, a grid algorithm was presented to optimize the gate location of injection mold on MDG. It deals with the massive high coupling task-blocks in collaborative way and reduces the times of the iteration efficiently. Examples have been conducted successfully by using the proposed grid algorithm on MDG, and results indicate that the proposed grid algorithm performs high speedup and efficiency.
Keywords :
genetic algorithms; grid computing; Globus Toolkits 4; complex injection mold optimization; four-layer mold design grid platform; grid algorithm; grid resources; information-entropy based searching technique; injection gate location optimization; injection mold optimization problems; multipopulation genetic strategy; resource sharing; Algorithm design and analysis; Application software; Bioinformatics; Collaboration; Computer industry; Design optimization; Grid computing; Large-scale systems; Oceans; Resource management; grid computing; mold design grid; optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
Type :
conf
DOI :
10.1109/CSO.2009.280
Filename :
5193636
Link To Document :
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