Simpler is Sometimes Better: A Dynamic Aero-Engine Calibration Study

Tong，Hao1,2; Zhang，Qingquan1,2; Hu，Chengpeng1,2; Feng，Xudong3; Wu，Feng4; Liu，Jialin1,2

10.1007/978-3-031-09726-3_31

2022

0302-9743

1611-3349

LECT NOTES ARTIF INT

13345 LNCS

343-352

Many real-world optimisation problems are in dynamic environments such that the search space and the optimum usually change over time. Various algorithms have been proposed in the literature to deal with such dynamic optimisation problems. In this paper, we focus on the dynamic aero-engine calibration, which is the process of optimising a group of parameters to ensure the performance of an aero-engine under an increasing number of different operation conditions. A real aero-engine is considered in this work. Three different types of strategies for tackling dynamic optimisation problems are compared in our empirical studies. The simplest strategy shows the superior performance which provide an interesting conclusion: Given a new dynamic optimisation problem, the algorithm with complex strategies and having excellent performance on benchmark problems is likely to be applied due to the lack of prior knowledge, however, the simplest restart strategy is sometimes well enough to solve real-world complex dynamic optimisation problems.

Dynamic optimisation Multi-swarm Particle swarm optimisation Real-world application Restart strategy

第一 ; 通讯

英语

EI

20223012407902

Aircraft engines ; Benchmarking ; Engines ; Particle swarm optimization (PSO)

Aircraft Engines, General:653.1 ; Computer Software, Data Handling and Applications:723 ; Optimization Techniques:921.5

2-s2.0-85134661810

Scopus

1.Research Institute of Trustworthy Autonomous System (RITAS),Southern University of Science and Technology,Shenzhen,China
2.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China
3.Xidian University,Xi’an,China
4.AECC,Chengdu,China

Tong，Hao,Zhang，Qingquan,Hu，Chengpeng,et al. Simpler is Sometimes Better: A Dynamic Aero-Engine Calibration Study[C],2022:343-352.