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Priority-Constraint Particle Swarm Optimization Algorithm for Dynamic Weapon-Target Assignment in Coordinated Air Combat
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AI
DOI：10.1142/s0129054126490031.png)
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Abstract
En 中文
Weapon-Target Assignment (WTA) is a cornerstone of coordinated air combat operations, where efficient allocation strategies are essential for mission success. This paper addresses the dynamic WTA problem by formulating a novel mathematical model that incorporates hard constraints on weapon allocation quantities to prevent resource wastage. To solve this complex optimization challenge, we propose a Priority-constrained Particle Swarm Optimization (PPSO) algorithm. Experimental results demonstrate that the PPSO algorithm not only achieves superior target assignment accuracy but also significantly minimizes weapon consumption. Furthermore, the algorithm exhibits robust adaptability to practical operational constraints, such as limited weapon inventory and fuel capacity, in cooperative air combat scenarios.
Keywords:
Cooperative air combat
weapon-target assignment
priority-constrained particle swarm optimization
dynamic optimization
Journal
I
IF:
0.6
Papers:
46
Citations:
0