DocumentCode
2261466
Title
Fuzzy Optimization Method Based on Dynamic Uncertainty Restriction
Author
Jin, Chenxia ; Li, Fachao
Author_Institution
Sch. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhuang
Volume
1
fYear
2008
fDate
20-22 Dec. 2008
Firstpage
736
Lastpage
740
Abstract
Fuzzy optimization is a well-known optimization problem in artificial intelligence, manufacturing and management, establishing general and operable fuzzy optimization methods are important in both theory and application. In this paper, by analyzing the essential characteristic of uncertain optimization, based on the idea of dynamic uncertainty criteria, we establish a fuzzy optimization model based on dynamic uncertainty restriction; then we give a solution method based on principal operation and dynamic uncertainty restriction (denoted by BPUO-FGA, for short), by combining with genetic algorithm; finally, we analyze the performance of BPUO-FGA by Markov chain theory and an example.
Keywords
Markov processes; fuzzy systems; genetic algorithms; uncertainty handling; BPUO-FGA; Markov chain theory; artificial intelligence; dynamic uncertainty restriction; fuzzy optimization method; genetic algorithm; Algorithm design and analysis; Artificial intelligence; Evolutionary computation; Fuzzy sets; Genetic algorithms; Information analysis; Optimization methods; Performance analysis; Technology management; Uncertainty; Fuzzy optimization; Markov chain; fuzzy genetic algorithm; principal operation; uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
Conference_Location
Shanghai
Print_ISBN
978-0-7695-3497-8
Type
conf
DOI
10.1109/IITA.2008.257
Filename
4739669
Link To Document