Genetic algorithm-based redundancy qptimization problems in fuzzy framework

Hou Fujun; Wu Qizong

doi:10.1080/03610920600728716

Genetic algorithm-based redundancy qptimization problems in fuzzy framework

Hou Fujun^*, Wu Qizong

^*Corresponding author for this work

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

This article uses a genetic algorithm to solve the series parallel redundancy optimization problem which is in a fuzzy framework. Three nonlinear chance constrained programing models and three goal programing models are formulated based on possibility measure and credibility measure. A fuzzy simulation-based genetic algorithm is then employed to solve these kinds of fuzzy programing. Finally, numerical examples are also given.

Original language	English
Pages (from-to)	1931-1941
Number of pages	11
Journal	Communications in Statistics - Theory and Methods
Volume	35
Issue number	10
DOIs	https://doi.org/10.1080/03610920600728716
Publication status	Published - 1 Oct 2006

Keywords

Credibility measure
Fuzzy simulation
Genetic algorithm
Possibility measure
Redundancy optimization

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10.1080/03610920600728716

Cite this

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abstract = "This article uses a genetic algorithm to solve the series parallel redundancy optimization problem which is in a fuzzy framework. Three nonlinear chance constrained programing models and three goal programing models are formulated based on possibility measure and credibility measure. A fuzzy simulation-based genetic algorithm is then employed to solve these kinds of fuzzy programing. Finally, numerical examples are also given.",

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AB - This article uses a genetic algorithm to solve the series parallel redundancy optimization problem which is in a fuzzy framework. Three nonlinear chance constrained programing models and three goal programing models are formulated based on possibility measure and credibility measure. A fuzzy simulation-based genetic algorithm is then employed to solve these kinds of fuzzy programing. Finally, numerical examples are also given.

KW - Credibility measure

KW - Fuzzy simulation

KW - Genetic algorithm

KW - Possibility measure

KW - Redundancy optimization

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Genetic algorithm-based redundancy qptimization problems in fuzzy framework

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Keywords

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