Multiobjective optimization using adaptive range genetic algorithms with data envelopment analysis

Masao Arakawa, Hirotaka Nakayama, Ichiro Hagiwara, Hiroshi Yamakawa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    23 Citations (Scopus)

    Abstract

    The present paper describe an implementation of the adaptive range genetic algorithms (ARange GAs) in multi-objective optimization by using the data envelopment analysis (DEA). ARange GAs is a new genetic search algorithms which adapt the searching range according to the optimization situation and make it possible to obtain highly accurate results effectively. DEA is to measure the efficiency of decision making units, and it is used mainly in the field of economy. When we combine both methods, we can obtain a great number of Pareto solutions, that might give an important aspect of the design, within a single GAs process effectively. The purpose of this study is to verify the characteristics and effectiveness of the proposed method through demonstrative examples.

    Original languageEnglish
    Title of host publication7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization
    PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
    Pages2074-2082
    Number of pages9
    Publication statusPublished - 1998
    Event7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 1998 - St. Louis, United States
    Duration: 1998 Sep 21998 Sep 4

    Other

    Other7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 1998
    CountryUnited States
    CitySt. Louis
    Period98/9/298/9/4

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    ASJC Scopus subject areas

    • Aerospace Engineering
    • Mechanical Engineering

    Cite this

    Arakawa, M., Nakayama, H., Hagiwara, I., & Yamakawa, H. (1998). Multiobjective optimization using adaptive range genetic algorithms with data envelopment analysis. In 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization (pp. 2074-2082). American Institute of Aeronautics and Astronautics Inc, AIAA.