By Topic

Fuzzy Optimization Method Based on Dynamic Uncertainty Restriction

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chenxia Jin ; Sch. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhuang ; Fachao Li

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.

Published in:

Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on  (Volume:1 )

Date of Conference:

20-22 Dec. 2008