Cart (Loading....) | Create Account
Close category search window
 

Parallel optimal statistical design method with response surface modelling using genetic algorithms

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 $31
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

4 Author(s)
Wu, A. ; Dept. of Electron. Eng., City Univ. of Hong Kong, Kowloon, Hong Kong ; Wu, K.Y. ; Chen, R.M.M. ; Shen, Y.

Genetic algorithms (GA) together with a boundary sampling strategy are proposed for optimal statistical design to achieve better performance and higher yield at minimum cost. Owing to the reduced number of circuit simulations, the proposed approach can provide a satisfactory model representation at improved computation speed for the selection of the response surface function approximation, Replacing circuit simulation with the proposed response function modelling method using GA, optimum statistical design is formulated as a problem that involves the solution procedures of design centring, fixed optimum tolerance assignment and variable optimum-tolerance assignment. To achieve better computational efficiency a number of approaches for paralleling the genetic algorithm operations are identified and studied. The parallel GA is implemented on a parallel machine constructed from a cluster of networked workstations. An optimum statistical design example is presented to show the effectiveness of the proposed techniques

Published in:

Circuits, Devices and Systems, IEE Proceedings -  (Volume:145 ,  Issue: 1 )

Date of Publication:

Feb 1998

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.