TY - JOUR
T1 - New ant colony algorithm and its application on optimization design of flight vehicle
AU - Che, Jing
AU - Tang, Shuo
AU - Wang, Wen Zheng
AU - He, Kai Feng
PY - 2009/2
Y1 - 2009/2
N2 - 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.
AB - 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.
KW - Aerodynamic configuration
KW - Continuous space
KW - Hypersonic cruise vehicle (HCV)
KW - Multi-objective ant colony algorithm (MACA)
KW - Optimization design
UR - https://www.scopus.com/pages/publications/62549136608
M3 - 文章
AN - SCOPUS:62549136608
SN - 1000-8055
VL - 24
SP - 262
EP - 268
JO - Hangkong Dongli Xuebao/Journal of Aerospace Power
JF - Hangkong Dongli Xuebao/Journal of Aerospace Power
IS - 2
ER -