DocumentCode :
498849
Title :
The optimization design of C2 Organization Communication Network based on nested genetic algorithm
Author :
Mu, Liang ; Xiu, Bao-xin ; Huang, Jin-cai ; Yao, Li
Author_Institution :
Sch. of Inf. Syst. & Manage., Nat. Univ. of Defence Technol., Changsha, China
Volume :
4
fYear :
2009
fDate :
12-15 July 2009
Firstpage :
1877
Lastpage :
1884
Abstract :
The task information flow oriented C2 organization communication network design problem (TIFOCOCNDP) is investigated. The basic information flow in the C2 organization is analyzed, then the performance measures and the calculation model of C2 organization communication network are studied. A constrained optimization model for TIFOCOCNDP is built, and a solution method based on genetic algorithm is proposed. Afterwards, a nested genetic algorithm for solving this problem is designed, analysis and design work involving encoding, crossover, mutation, fitness function construction and algorithm nestification, etc. is carried out. In the final section of the paper, a case is presented to test the feasibility of the solution method. The validity of the genetic algorithm is analyzed through computational experiments.
Keywords :
genetic algorithms; information management; organisational aspects; C2 organization communication network design problem; computational experiments; constrained optimization model; nested genetic algorithm; optimization design; task information flow; Algorithm design and analysis; Communication networks; Constraint optimization; Design optimization; Encoding; Fluid flow measurement; Genetic algorithms; Genetic mutations; Information analysis; Performance analysis; Nested genetic algorithm; Organization communication network; Task information flow;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
Type :
conf
DOI :
10.1109/ICMLC.2009.5212200
Filename :
5212200
Link To Document :
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