Journal of System Simulation
Abstract
Abstract: In order to solve the problem that exploratory simulation can not traverse the solution space quickly, and provide the auxiliary decision-making scheme in real time, a genetic algorithm based on classifier is proposed. The framework of simulation optimization method based on the algorithm is established. It can find the optimal solution according to the dynamic changes of key factors and decision targets of the system, which is suitable for such as seeking the best efficiency-cost ratio scheme and the optimization of the optimal power deployment and other systems. Based on the simulation bed system of the National Defense University, experiments on fire blocking operations in a sea area are carried out. The power allocation problem is optimized by GABC (genetic algorithm based on classifier). The experiment shows that the method can find the most efficient and cost ratio scheme from the complex system constraints accurately and quickly, and can reduce the number of simulation experiments and meet the needs of quick assistant commander decision.
Recommended Citation
Zhang, Hucheng and Yang, Jingyu
(2023)
"Research on Intelligent Optimization Method of Combat SoS Based on GABC Algorithm,"
Journal of System Simulation: Vol. 35:
Iss.
1, Article 19.
DOI: 10.16182/j.issn1004731x.joss.21-0666
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol35/iss1/19
First Page
221
Revised Date
2021-09-04
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.21-0666
Last Page
227
CLC
TP391.9
Recommended Citation
Hucheng Zhang, Jingyu Yang. Research on Intelligent Optimization Method of Combat SoS Based on GABC Algorithm[J]. Journal of System Simulation, 2023, 35(1): 221-227.
DOI
10.16182/j.issn1004731x.joss.21-0666
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