Abstract
The observation time on the target is usually uncertain due to the complexity and uncertainty of reconnaissance missions. The multiple unmanned aerial vehicles (UAVs) reconnaissance problem with a stochastic observation time (MURSOT) is modeled as a multi-objective optimal routing problem including minimizing mission duration, total time and fleet size. For solving this problem, a multi-objective local search is incorporated to a steady-state multi-objective evolutionary algorithm (MOEA) with ε-dominance conception (epsMOEA). Besides, several heuristic genetic operations using the insert-to-nearest method (INM) are proposed. Experimental results show that the proposed method is effective on MURSOT and its superiority is more remarkable with the growth of the size of missions.
| Original language | English |
|---|---|
| Pages (from-to) | 326-331 |
| Number of pages | 6 |
| Journal | Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics |
| Volume | 32 |
| Issue number | 2 |
| State | Published - Feb 2010 |
Keywords
- Heuristic genetic operation
- Hybrid multi-objective evolutionary algorithm
- Routing problem
- Unmanned aerial vehicle
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