Simulation Research on Multi-aircraft Conflict Resolution Based on Improved Chaotic Ant Colony Algorithm

doi:10.16182/j.issn1004731x.joss.23-1117

Abstract

Abstract:

A chaotic ant colony algorithm based on dynamic volatility factor is proposed to solve the problem of multi-aircraft conflict resolution during free flight of fighter jets. The mathematical modelling is conducted on the conflict resolution problem of multiple fighter jets in the air. Based on the performance characteristics of fighter jets, fighter protection zone models, flight conflict models, and resolution models are established respectively. The chaotic ant colony algorithm is improved by using Logistic mapping and Henon mapping to optimize the pheromone update formula in the ant colony algorithm, and setting a dynamic factor for the pheromone volatilization factor to improve search efficiency at different stages. The typical 2-aircrafts, 4-aircrafts, and 6-aircrafts flight conflict scenarios are set up to simulate and verify the effectiveness of the algorithm. The results show that the optimized algorithm is feasible, and all performance indicators of the algorithm are improved.

Key words: chaos algorithm, ant colony algorithm, multi-aircraft flight conflict resolution, chaotic mapping, dynamic factor

CLC Number:

TP391.9

Tong Liang, Yang Jie, Gan Xusheng, Shen Di, Yang Wenda, Chen Daxiong. Simulation Research on Multi-aircraft Conflict Resolution Based on Improved Chaotic Ant Colony Algorithm[J]. Journal of System Simulation, 2025, 37(1): 155-166.

Figures/Tables 16

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Table 1

Simulation parameter setting

参数	量值
$M$	60
$a c i c_m a x$	50
$Q$	500
$ρ m a x$	0.9
$ρ m i n$	0.2
$ρ 0$	0.5
$δ m i n$	2

Table 1

Fig. 8

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Table 2

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