Multidisciplinary design optimization of aircraft wing planform based on evolutionary algorithms

Shigeru Obayashi

Multidisciplinary design optimization of aircraft wing planform based on evolutionary algorithms

Shigeru Obayashi

Creative Flow Research Division

Research output: Contribution to journal › Conference article › peer-review

41 Citations (Scopus)

Abstract

This paper examines the evolutionary approach for aircraft design optimization. Several niching and elitist models are first applied to Multiple-Objective Genetic Algorithms (MOGAs). Numerical results suggest that the combination of the fitness sharing and the best-N selection leads to the best performance. The resulting MOGA is then applied to multidisciplinary design optimization problems of transonic and supersonic wing platform shapes. The results confirm the feasibility of the present approach.

Original language	English
Pages (from-to)	3148-3153
Number of pages	6
Journal	Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume	4
Publication status	Published - 1998 Dec 1
Event	Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - San Diego, CA, USA Duration: 1998 Oct 11 → 1998 Oct 14

ASJC Scopus subject areas

Hardware and Architecture
Control and Systems Engineering

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abstract = "This paper examines the evolutionary approach for aircraft design optimization. Several niching and elitist models are first applied to Multiple-Objective Genetic Algorithms (MOGAs). Numerical results suggest that the combination of the fitness sharing and the best-N selection leads to the best performance. The resulting MOGA is then applied to multidisciplinary design optimization problems of transonic and supersonic wing platform shapes. The results confirm the feasibility of the present approach.",

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AB - This paper examines the evolutionary approach for aircraft design optimization. Several niching and elitist models are first applied to Multiple-Objective Genetic Algorithms (MOGAs). Numerical results suggest that the combination of the fitness sharing and the best-N selection leads to the best performance. The resulting MOGA is then applied to multidisciplinary design optimization problems of transonic and supersonic wing platform shapes. The results confirm the feasibility of the present approach.

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T2 - Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5)

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