DocumentCode :
3439357
Title :
The adaptive optimization of C2 organization decision layer structure based on nested improved simulated annealing algorithm
Author :
Mu, Liang ; Feng, Yang-he ; Zhang, Wei-Ming ; Xiu, Bao-xin
Author_Institution :
Eng. Lab., Nat. Univ. of Defense Technol., Changsha, China
Volume :
3
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
682
Lastpage :
687
Abstract :
The C2 organization decision layer structure adaptive optimization problem (DLSAOP) is studied. Three C2 organization decision layer structure (DLS) performance measures, including decision workload, decision quality and decision gain, are presented. Then a constrained optimization model for DLSAOP is established. DLSAOP is a novel combinational optimization problem with strong constraints and two variants. A nested improved simulated annealing (NISA) algorithm is designed for the problem. The standard simulated annealing (SA) algorithm has shortcomings of poor convergence, local repeatedly searching and early stagnation under strong constraints, for which diversified temperature controlling, tabu object and evaluation function containing items of constraint-violate-punishment are incorporated into NISA. A nesting approach is presented to combine the two improved SA algorithms for the two variants. At last, the computational experiment illustrates that DLSAOP modeling and optimization can remarkably improve DLS performance and the result of NISA has better quality and stability than other algorithms.
Keywords :
command and control systems; decision making; simulated annealing; C2 organization decision layer structure; adaptive optimization; command control organization; constrained optimization model; nested improved simulated annealing algorithm; Adaptation model; Annealing; Computational modeling; Delta modulation; Gallium; Variable speed drives; Adaptive Optimization; C2 Organization Decision Layer Structure; Nested Improved Simulated Annealing Algorithm; Performance Measure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
Type :
conf
DOI :
10.1109/ICICISYS.2010.5658279
Filename :
5658279
Link To Document :
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