Solving multi-response optimization problem using artificial neural network and PCR-VIKOR

Author

Bashiri, Mahdi ; Geranmayeh, Amir Farshbaf ; Sherafati, Mahtab

Author_Institution

Dept. of Ind. Eng., Shahed Univ., Tehran, Iran

fYear

2012

fDate

15-18 June 2012

Firstpage

1033

Lastpage

1038

Abstract

In this paper a hybrid approach is introduced to solve multiple response problems. In the proposed method signal to noise (SN) ratio is computed and then SN ratios for unexperimented treatments are estimated using artificial neural network. The SN ratios are converted into a process performance index by applying process capability ratio and VIKOR method, so the treatments can be ranked and the best of them is selected. The performance of the proposed method is verified in a case study. Moreover a sensitivity analysis has been done by a VIKOR score estimator turned neural network. The results show efficiency of the proposed approach.

Keywords

mathematics computing; neural nets; optimisation; sensitivity analysis; PCR-VIKOR; VIKOR score estimator turned neural network; Vlse Kriterijumska Optimizacija I Kompromisno Resenje method; artificial neural network; hybrid approach; multiresponse optimization problem; process capability ratio; process performance index; sensitivity analysis; signal to noise ratio; Artificial neural networks; Biological neural networks; Equations; Indexes; Optimization; Sensitivity analysis; Tin; Taguchi; VIKOR method; artificial neural network; multiresponse optimization; process capability ratio (PCR);

fLanguage

English

Publisher

ieee

Conference_Titel

Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4673-0786-4

Type

conf

DOI

10.1109/ICQR2MSE.2012.6246399

Filename

6246399