Empirical comparisons of gradient-based methods on an engine-inlet shape optimization problem


Sóbester, András and Keane, Andy J. (2002) Empirical comparisons of gradient-based methods on an engine-inlet shape optimization problem In Proceedings of the 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization. American Institute of Aeronautics and Astronautics. 11 pp.

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Description/Abstract

With the development of increasingly sophisticated adjoint flow-solvers capable of providing objective function gradients at reasonable computational costs, modern deterministic gradient-based search methods have come to be regarded as amongst the most powerful tools in aerodynamic shape optimization and MDO problems. However, their performance can be disappointing when the objective function landscape features multiple local optima, long valleys, noise or discontinuities. Equally, stochastic global explorers, such as Genetic Algorithms (GAs), while less affected by these problems, are relatively slow to converge. In this paper we propose GLOSSY (Global/Local Search Strategy), a generic hybrid approach, which combines a global exploration method with gradient-based exploitation. We analyze the performance of two optimizers based on the GLOSSY framework (fusing a GA with a quasi-Newton local search method) and we show through a set of comparative tests that on the moderately noisy objective landscape of a jet-engine inlet shape optimization problem the hybrid outperforms both of its components used individually. We also look at the issue of what global / local search effort ratio gives the hybrid the best performance.

Item Type: Conference or Workshop Item (Paper)
Additional Information: CD-ROM
Venue - Dates: 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 2002-09-04 - 2002-09-06
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ePrint ID: 23052
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Date Event
2002Published
Date Deposited: 07 Mar 2007
Last Modified: 16 Apr 2017 22:47
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/23052

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