@inproceedings{6d060dfd8bf14595b6b541ff93be6b84,
title = "Studies on the application of MOEA/D to aerodynamic optimization design",
abstract = "Aerodynamic multi-objective optimization problem (AMOP) is common in aerodynamic optimization design (AOD). Multi-Objective Evolutionary Algorithms (MOEAs) are popular to solve AMOPs since they can obtain a set of solutions called Pareto optimal in a single run. Since numerically evaluating the objective of AOD is generally computationally expensive and time consuming, improving the convergence performance of MOEAs and focusing the computational resource on the solutions that the decision maker (DM) most interested in are two important aspects to solve AMOP better. An improved multi-objective evolutionary algorithm based on decomposition using a combined operator is used to improve the convergence performance. Several methods of solving AMOP considering the DM's preference are also discussed which focus the computational efforts on the Pareto solutions that suit the DM's preference better. Multi-objective test functions and aerodynamic optimization design of airfoil is tested. The results show that the improved algorithm is capable to solve AMOPs with user preference, and converge faster than the original algorithm.",
keywords = "CMA-ES, MOEA/D, Multi-objective aerodynamic optimization design, Preference",
author = "Xinqi Zhu and Zhenghong Gao and Zhiwei Chen",
note = "Publisher Copyright: {\textcopyright} 31st Congress of the International Council of the Aeronautical Sciences, ICAS 2018. All rights reserved.; 31st Congress of the International Council of the Aeronautical Sciences, ICAS 2018 ; Conference date: 09-09-2018 Through 14-09-2018",
year = "2018",
language = "英语",
series = "31st Congress of the International Council of the Aeronautical Sciences, ICAS 2018",
publisher = "International Council of the Aeronautical Sciences",
booktitle = "31st Congress of the International Council of the Aeronautical Sciences, ICAS 2018",
}