Title :
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
fDate :
6/21/1905 12:00:00 AM
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location :
Tokyo
Print_ISBN :
0-7803-5731-0
DOI :
10.1109/ICSMC.1999.823266
