Abstract
Aiming at the dynamic target assignment problem in anti-ground mission of an unmanned combat aerial vehicle (UCAV) fleet, a weapon target assignment (WTA) model for associated targets is built up. A memory enhanced dynamic univariate marginal distribution algorithm (MDUMDA) is proposed to solve the problem at hand. In this algorithm, the probability model is utilized to save and reuse the historic evolutionary information. Simulation results show that the WTA model is reasonable, the MDUMDA can effectively solve dynamic WTA, and its performance is significantly better than the random immigration algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 2166-2170 |
| Number of pages | 5 |
| Journal | Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics |
| Volume | 32 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 10 Reduced Inequalities
Keywords
- Dynamic univariate marginal distribution algorithm (UMDA)
- Dynamic weapon target assignment (WTA)
- Memory method
- Unmanned combat aerial vehicle (UCAV) fleet
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