Possibilistic Stackelberg solutions to bilevel linear programming problems with fuzzy parameters
Hideki Katagiri, Kosuke Kato, Takeshi Uno
Abstract
Hideki Katagiri, Kosuke Kato, Takeshi Uno
Abstract
This article considers bilevel linear programming problems where the coefficients of the objective functions and the constraints in the problem are given as fuzzy parameters. Stackelberg solutions under fuzziness are defined by incorporating the notions of possibility theory into the original concept of Stackelberg solutions. It is shown that Stackelberg problems under fuzziness are transformed into deterministic bilevel linear or nonlinear programming problems, and that the resulting problems are exactly solved by using conventional bilevel linear or nonlinear programming techniques.
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This article considers bilevel linear programming problems where the coefficients of the objective functions and the constraints in the problem are given as fuzzy parameters. Stackelberg solutions under fuzziness are defined by incorporating the notions of possibility theory into the original concept of Stackelberg solutions. It is shown that Stackelberg problems under fuzziness are transformed into deterministic bilevel linear or nonlinear programming problems, and that the resulting problems are exactly solved by using conventional bilevel linear or nonlinear programming techniques.
Key concepts: Bilevel optimization, Stackelberg competition, Mathematical optimization, Linear programming, Fuzzy logic, Nonlinear system, Nonlinear programming, Computer science