By Topic

Weight coefficient cluster covering genetic algorithm for multi-objective optimization based on accurate and fuzzy decoding

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

3 Author(s)
Yan Cao ; Sch. of Mechatron. Eng., Xi''an Technol. Univ., Xi''an, China ; Hui Yao ; Ning Liu

A novel weight coefficient cluster covering genetic algorithm for multi-objective optimization and its implementation based on Delphi 7.0 are discussed. First, the principle and key technologies of the algorithm are presented, including cluster covering, accurate decoding and fuzzy decoding, etc. Then, its workflow is analyzed. Its main modules include input module, computing module, output module, and operational module. Its operational process is illustrated. The influence of algorithm parameters on computing results is also analyzed. The results show that the algorithm is validated. The algorithm can adopt several computing patterns. Both accurate decoding and fuzzy decoding have good astringency and diversity distribution. It is easy to use and its visualized result analyzing sub-system can output both data and graphs. The alternative employment of accurate decoding and fuzzy decoding can further improve its performance. These instructions give you basic guidelines for preparing papers for conference proceedings.

Published in:

Circuits,Communications and System (PACCS), 2010 Second Pacific-Asia Conference on  (Volume:2 )

Date of Conference:

1-2 Aug. 2010