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Dynamic Weapon-Target Assignment (DWTA) Using the Particle Swarm Optimization (PSO) Algorithm
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Ali Jafari *   , Abolfazl Asghari |
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Abstract: (29 Views) |
In modern warfare, it is essential for commanders to assess battlefield conditions and make appropriate decisions to counter enemy forces. Thus, a system is required to assist commanders in decision-making. This highlights the significance of the Dynamic Weapon-Target Assignment (DWTA) problem in command and control. In this paper, a close-combat battlefield scenario is first proposed, which has not been addressed in any prior research. Subsequently, a method based on the Particle Swarm Optimization (PSO) algorithm is presented, capable of solving the DWTA problem tailored to the proposed scenario. The suggested method effectively resolves the issue of becoming trapped in local optima. While most existing approaches to DWTA focus solely on weapon platforms and threats, the method introduced in this paper additionally incorporates assets into consideration. Finally, the proposed method is evaluated and compared with other methods on two distinct scenarios, with results demonstrating its superior performance.
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| Keywords: Particle Swarm Optimization Algorithm, Local Optima, Dynamic Weapon-Target Assignment (DWTA), Assets, Command and Control |
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Full-Text [PDF 1322 kb]
(12 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2025/05/10 | Accepted: 2025/11/30 | Published: 2026/09/19
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