Simulation-Based Optimization on the System-of-Systems Model via Model Transformation and Genetic Algorithm: A Case Study of Network-Centric Warfare

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Simulation of a system-of-systems (SoS) model, which consists of a combat model and a network model, has been used to analyze the performance of network-centric warfare in detail. However, finding the combat model parameters satisfying the required combat power using simulation can take a long time for two reasons: (1) the prolonged execution time per simulation run and (2) the enormous number of simulation runs. This paper proposes a simulation-based optimization method for the SoS-based simulation model to overcome these problems. The method consists of two processes: (1) the transformation of the SoS-based model into an integrated model using the neural network to reduce the execution time and (2) the optimization of the integrated model using the genetic algorithm with ranking and selection to decrease the number of simulation runs. The experimental result reveals that the proposed method significantly reduced the time for finding the optimal combat parameters with an acceptable level of accuracy.
Publisher
WILEY-HINDAWI
Issue Date
2018-10
Language
English
Article Type
Article
Citation

COMPLEXITY

ISSN
1076-2787
DOI
10.1155/2018/4521672
URI
http://hdl.handle.net/10203/246545
Appears in Collection
EE-Journal Papers(저널논문)
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