New multiobjective fuzzy optimization method and its application

Takanori Kiyota, Yasutaka Tsuji, Eiji Kondo

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

This paper proposes a new multiobjective fuzzy optimization method. First, the unsatisfying function, which is more useful and effective as the expression of fuzziness for optimization problems than the membership function, is introduced. The multiobjective optimization problem is transformed into a satisfying problem by using aspiration levels, and the fuzzy satisfying problem is formulated. Then, the interactive design method to minimize the maximum unsatisfaction rating by genetic algorithm is proposed. The effectiveness of the proposed method is demonstrated by the design example of an active suspension system. The trade-off graph is used in order to seek a satisfying solution, which reflects the designer's preference, more interactively and graphically.

Original languageEnglish
Article number877017
Pages (from-to)4224-4228
Number of pages5
JournalProceedings of the American Control Conference
Volume6
DOIs
Publication statusPublished - Dec 1 2000

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Active suspension systems
Membership functions
Multiobjective optimization
Genetic algorithms

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

New multiobjective fuzzy optimization method and its application. / Kiyota, Takanori; Tsuji, Yasutaka; Kondo, Eiji.

In: Proceedings of the American Control Conference, Vol. 6, 877017, 01.12.2000, p. 4224-4228.

Research output: Contribution to journalArticle

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