An interactive fuzzy satisficing approach using genetic algorithm for multi-objective problems

Takanori Kiyota; Yasutaka Tsuji; Eiji Kondo

An interactive fuzzy satisficing approach using genetic algorithm for multi-objective problems

Takanori Kiyota, Yasutaka Tsuji, Eiji Kondo

Control Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

This paper describes a fuzzy satisficing method for multi-objective optimization problems using Genetic Algorithm (GA). A multi-objective design problem with constraints is expressed as a satisficing problem of constraints by introducing an aspiration level for each objective. Here, in order to handle fuzziness involved in aspiration levels and constraints, the unsatisfying function is introduced, and the problem is formulated as a multi-objective minimization problem of unsatisfaction ratings. As the optimization method, GA is employed. He/She can seek a satisficing solution by modifying parameters interactively according to his/her preferences.

Original language	English
Title of host publication	Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS
Editors	M.H. Smith, W.A. Gruver, L.O. Hall
Pages	757-762
Number of pages	6
Volume	2
Publication status	Published - 2001
Event	Joint 9th IFSA World Congress and 20th NAFIPS International Conference - Vancouver, BC, Canada Duration: Jul 25 2001 → Jul 28 2001

Other

Other	Joint 9th IFSA World Congress and 20th NAFIPS International Conference
Country/Territory	Canada
City	Vancouver, BC
Period	7/25/01 → 7/28/01

All Science Journal Classification (ASJC) codes

Computer Science(all)
Media Technology

Cite this

An interactive fuzzy satisficing approach using genetic algorithm for multi-objective problems. / Kiyota, Takanori; Tsuji, Yasutaka; Kondo, Eiji.
Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS. ed. / M.H. Smith; W.A. Gruver; L.O. Hall. Vol. 2 2001. p. 757-762.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kiyota, T, Tsuji, Y & Kondo, E 2001, An interactive fuzzy satisficing approach using genetic algorithm for multi-objective problems. in MH Smith, WA Gruver & LO Hall (eds), Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS. vol. 2, pp. 757-762, Joint 9th IFSA World Congress and 20th NAFIPS International Conference, Vancouver, BC, Canada, 7/25/01.

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AB - This paper describes a fuzzy satisficing method for multi-objective optimization problems using Genetic Algorithm (GA). A multi-objective design problem with constraints is expressed as a satisficing problem of constraints by introducing an aspiration level for each objective. Here, in order to handle fuzziness involved in aspiration levels and constraints, the unsatisfying function is introduced, and the problem is formulated as a multi-objective minimization problem of unsatisfaction ratings. As the optimization method, GA is employed. He/She can seek a satisficing solution by modifying parameters interactively according to his/her preferences.

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T2 - Joint 9th IFSA World Congress and 20th NAFIPS International Conference

Y2 - 25 July 2001 through 28 July 2001

ER -

An interactive fuzzy satisficing approach using genetic algorithm for multi-objective problems

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