Pseudo-optimal solutions of FLP problems by using the Cumulative Membership Function.

Author

García, Juan Carlos Figueroa ; Bello, Cesar Amilcar Lopez

Author_Institution

Lab. for Autom., Microelectron. & Comput. Intell. (LAMIC), Univ. Distrital Francisco Jose de Caldas, Bogota, Colombia

fYear

2009

fDate

14-17 June 2009

Firstpage

1

Lastpage

6

Abstract

This paper shows an alternative method to find optimal solutions of a fuzzy linear programming (FLP) problems. The classical FLP problem is treated by using fuzzy restrictions in the form Ax les b where indicates a type-1 fuzzy set (T1 FS). The proposed approach uses joint A and b fuzzy parameters to solve a FLP model. Nonlinear membership functions are used to represent imprecisions in their parameters and the cumulative membership function (CMF) is used to solve the problem by means of an alpha-cut approach.

Keywords

fuzzy set theory; linear programming; nonlinear programming; alpha-cut approach; cumulative membership function; fuzzy linear programming problems; fuzzy restrictions; nonlinear membership functions; pseudo-optimal solutions; type-1 fuzzy set; Automation; Computational intelligence; Computer industry; Fuzzy logic; Fuzzy sets; Information processing; Laboratories; Linear programming; Mathematical model; Microelectronics;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society, 2009. NAFIPS 2009. Annual Meeting of the North American

Conference_Location

Cincinnati, OH

Print_ISBN

978-1-4244-4575-2

Electronic_ISBN

978-1-4244-4577-6

Type

conf

DOI

10.1109/NAFIPS.2009.5156464

Filename

5156464