Abstract
Ant colony algorithm (ACA) is a new bionic optimization algorithm developed in recent years. With global and efficient characteristics, it has been applied in discontinuous space successfully. To introduce it to aircraft design field, a high dimensional, multi-objective and multi-restrained ACA for continuous space was built. In an example, it was applied to the multi-objective optimization design of aerodynamic configuration for hypersonic cruise vehicle (HCV). Through comparison with Pareto genetic algorithms (GA), ACA shows its advantage. Finally, from our research work, ACA has great reference values for complex, multidimensional and large-scale optimization problems in aircraft design field.
| Original language | English |
|---|---|
| Pages (from-to) | 262-268 |
| Number of pages | 7 |
| Journal | Hangkong Dongli Xuebao/Journal of Aerospace Power |
| Volume | 24 |
| Issue number | 2 |
| State | Published - Feb 2009 |
Keywords
- Aerodynamic configuration
- Continuous space
- Hypersonic cruise vehicle (HCV)
- Multi-objective ant colony algorithm (MACA)
- Optimization design
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