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Managing approximate models in evolutionary aerodynamic design optimization

Jin, Y, Olhofer, M and Sendhoff, B (2001) Managing approximate models in evolutionary aerodynamic design optimization In: 2001 IEEE Conference on Evolutionary Computation, ICEC, 2001-05-27 - 2001-05-30.

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Approximate models have to be used in evolutionary optimization when the original fitness function is computationally very expensive. Unfortunately, the convergence property of the evolutionary algorithm is unclear when an approximate model is used for fitness evaluation because approximation errors are involved in the model. What is worse, the approximate model may introduce false optima that lead the evolutionary algorithm to a wrong solution. To address this problem, individual and generation based evolution control are introduced to ensure that the evolutionary algorithm using approximate fitness functions will converge correctly. A framework for managing approximate models in generation-based evolution control is proposed. This framework is well suited for parallel evolutionary optimization in which evaluation of the fitness function is time-consuming. Simulations on two bench-mark problems and one example of aerodynamic design optimization demonstrate that the proposed algorithm is able to achieve a correct solution as well as a significantly reduced computation time.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Computing Science
Authors :
Jin, Y
Olhofer, M
Sendhoff, B
Date : 2001
DOI : 10.1109/CEC.2001.934445
Contributors :
Additional Information : © 2001 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 13 Jul 2012 10:33
Last Modified : 31 Oct 2017 14:35

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