Finding tradeoffs by using multiobjective optimization algorithms

Shigeru Obayashi; Daisuke Sasaki; Akira Oyama

doi:10.2322/tjsass.47.51

Finding tradeoffs by using multiobjective optimization algorithms

Shigeru Obayashi, Daisuke Sasaki, Akira Oyama

Creative Flow Research Division

Research output: Contribution to journal › Article › peer-review

23 Citations (Scopus)

Abstract

The objective of the present study is to demonstrate performances of Evolutionary Algorithms (EAs) and conventional gradient-based methods for finding Pareto fronts. The multiobjective optimization algorithms are applied to analytical test problems as well as to the real-world problems of a compressor design. The comparison results clearly indicate the superiority of EAs in finding tradeoffs.

Original language	English
Pages (from-to)	51-58
Number of pages	8
Journal	Transactions of the Japan Society for Aeronautical and Space Sciences
Volume	47
Issue number	155
DOIs	https://doi.org/10.2322/tjsass.47.51
Publication status	Published - 2004 May

Keywords

Aerodynamics
CFD
Compressor
Design
Evolutionary Computation
Gradient-Based Method
Multiobjective Optimization

ASJC Scopus subject areas

Aerospace Engineering
Space and Planetary Science

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10.2322/tjsass.47.51

Cite this

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AU - Sasaki, Daisuke

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AB - The objective of the present study is to demonstrate performances of Evolutionary Algorithms (EAs) and conventional gradient-based methods for finding Pareto fronts. The multiobjective optimization algorithms are applied to analytical test problems as well as to the real-world problems of a compressor design. The comparison results clearly indicate the superiority of EAs in finding tradeoffs.

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KW - Design

KW - Evolutionary Computation

KW - Gradient-Based Method

KW - Multiobjective Optimization

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Finding tradeoffs by using multiobjective optimization algorithms

Abstract

Keywords

ASJC Scopus subject areas

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