DocumentCode :
3474401
Title :
Game theoretical framework for process plan decision of jobs in networked manufacturing
Author :
Zhou, Guanghui ; Jiang, Pingyu ; Zhang, Guohai
Author_Institution :
State Key Lab. for Manuf. Syst. Eng., Xian
fYear :
2007
fDate :
18-21 Aug. 2007
Firstpage :
1868
Lastpage :
1873
Abstract :
In this paper, we describe a new methodology based on game theory for optimal process plan decision of jobs in networked manufacturing environment. The main contribution of this study can be focused on modeling a game theoretic framework for optimal process plan decision problem to analyze strategic behaviors of multiple jobs. The optimal process plan decision problem is formulated as a non-cooperative game with complete information. This game is divided into two sub games named process plan decision sub game and job scheduling sub game. The former provides the latter with players while the latter provides the former with payoff values. Endeavoring to solve this game more efficiently and effectively, a two-level nested solution algorithm using Genetic Algorithm (GA) is proposed. A numerical example is presented to investigate the feasibility of the above approach.
Keywords :
game theory; genetic algorithms; integrated manufacturing systems; job shop scheduling; process planning; decision problem; game theory; genetic algorithm; job scheduling; networked manufacturing environment; noncooperative game; optimal process plan decision; strategic behavior; Computer aided manufacturing; Game theory; Genetic algorithms; Globalization; Job shop scheduling; Manufacturing automation; Manufacturing processes; Process planning; Pulp manufacturing; Virtual manufacturing; Game theory; Genetic algorithm; Networked manufacturing; Process plan decision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
Type :
conf
DOI :
10.1109/ICAL.2007.4338878
Filename :
4338878
Link To Document :
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