ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Kriging?based mixed?integer optimization method using sample mapping mechanism for flight vehicle design
Received date: 2023-03-21
Revised date: 2023-04-25
Accepted date: 2023-05-26
Online published: 2023-06-02
To deal with the problems of high computational cost and poor global convergence that often exist in discretecontinuous mixed optimization of complex flight vehicle systems， a Sample Mapping and Dynamic Kriging based Discrete-Continuous Mixed Optimization method （SMDK-DC） is proposed. In this method， time-consuming simulation model is replaced by Kriging surrogate model to reduce computational expenses. A sample point mapping mechanism based on generalized Manhattan distance criterion is also proposed to efficiently generate uniformly-distributed real sample points in continuous-discrete domain. Expected improvement criteria is combined with significant sampling space to identify new sample points，update Kriging continuously and dynamically， and guide the rapid convergence of the discrete-continuous optimization process. Benchmark cases show that compared with international methods such as SOMI and NOMAD， SMDK-DC has significant advantages in global convergence and robustness. Finally， SMDK-DC is used for solving a multidisciplinary design optimization problem of solid rocket motor. The method， on the premise of satisfying all the constraints of the combustion chamber and internal ballistic discipline， leads to a total impulse increase of at least 12. 92%， and the optimization yield is 1. 71% higher than that of SOMI， which verifying the effectiveness and engineering practicability of SMDK-DC.
Haoda LI , Teng LONG , Renhe SHI , Nianhui YE . Kriging?based mixed?integer optimization method using sample mapping mechanism for flight vehicle design[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2024 , 45(3) : 228726 -228726 . DOI: 10.7527/S1000-6893.2023.28726
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