Application of genetic algorithm for response surface modeling in optimal statistical design

Author

Shen, Y. ; Chen, R.M.M.

Author_Institution

Dept. of Electron. Eng., City Polytech. of Hong Kong, Kowloon, Hong Kong

Volume

3

fYear

1995

fDate

30 Apr-3 May 1995

Firstpage

2152

Abstract

In this paper, a new approach for optimal statistical design to achieve 100% yield at minimum cost is introduced. A kind of genetic algorithm together with a boundary sampling strategy is proposed for the selection of the response surface model function to achieve better accuracy of the model representation and improved computation speed due to reduced number of circuit simulations. The complete optimum statistic design also involves the solution procedure of design centering fixed and variable optimum tolerance assignment. A numerical example is presented to show the effectiveness of the new technique

Keywords

circuit analysis computing; circuit optimisation; genetic algorithms; integrated circuit yield; tolerance analysis; boundary sampling strategy; circuit simulation; computation speed; design centering; genetic algorithm; optimal statistical design; response surface modeling; tolerance assignment; yield; Algorithm design and analysis; Circuit simulation; Cost function; Design engineering; Genetic algorithms; Monte Carlo methods; Polynomials; Response surface methodology; Sampling methods; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on

Conference_Location

Seattle, WA

Print_ISBN

0-7803-2570-2

Type

conf

DOI

10.1109/ISCAS.1995.523852

Filename

523852