Application of multiobjective optimization and neural network techniques to process design

Author

Kadambaya, Zato ; Pattipati, Krishna R.

Author_Institution

Dept. of Electr. & Syst. Eng., Connecticut Univ., Storrs, CT, USA

Volume

3

fYear

1999

fDate

6/21/1905 12:00:00 AM

Firstpage

527

Abstract

A major problem in product development is the selection of a set of conditions (parameters) which will result in a product with desirable performance. This problem is even more significant when optimizing multiple responses under a common set of constraints. This paper addresses the application of multiobjective optimization (MOP) techniques to process optimization where processes are represented using regression or neural network (NN) models. The application of MOP using regression and NN process modeling techniques is demonstrated through two examples

Keywords

neural nets; optimisation; product development; statistical analysis; constraints; multiobjective optimization techniques; multiple response optimization; neural network models; process design; process optimization; product development; regression models; Constraint optimization; Design optimization; Mathematical model; Neural networks; Neurons; Process design; Product development; Response surface methodology; Systems engineering and theory; USA Councils;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on

Conference_Location

Tokyo

ISSN

1062-922X

Print_ISBN

0-7803-5731-0

Type

conf

DOI

10.1109/ICSMC.1999.823266

Filename

823266