Journal of System Simulation
Abstract
Abstract: Ant Colony Optimization (ACO) is a new intelligence optimization algorithm. When applied to jamming resource allocation, the velocity of convergence in optimization process is slow and the probability of obtaining the global optimal solution is low. In order to raise the efficiency of jamming resource allocation and the probability of getting global optimal solution, the attenuation factor is improved to a variable that changes according to the exponential function in optimization process. The attenuation factor is taken as a relatively small value in the initial search phase, and increases monotonically and exponentially as the number of iterations increases. Simulation results illustrate the effectiveness of the proposed method, the high efficiency of jamming resource allocation, and higher global optimal solution acquisition probability.
Recommended Citation
Wang, Qingyun; Jiao, Dezhong; Shuo, Shi; Peng, Genyan; Sun, Junhua; and Duan, Yuxin
(2022)
"Improved Ant Colony Optimization Algorithm for Jamming Resource Allocation,"
Journal of System Simulation: Vol. 33:
Iss.
12, Article 21.
DOI: 10.16182/j.issn1004731x.joss.20-FZ0812E
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol33/iss12/21
First Page
2967
Revised Date
2021-08-11
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.20-FZ0812E
Last Page
2974
CLC
TP391.9
Recommended Citation
Wang Qingyun, Jiao Dezhong, Shi Shuo, Peng Genyan, Sun Junhua, Duan Yuxin. Improved Ant Colony Optimization Algorithm for Jamming Resource Allocation[J]. Journal of System Simulation, 2021, 33(12): 2967-2974.
DOI
10.16182/j.issn1004731x.joss.20-FZ0812E
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