EN
TR
MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH
Abstract
The most widely used approach for solving multi response surface problems is response surface methodology. It is thought to be that the response surface methodology is inadequate for evaluation of unexplained vagueness in real world problems. Therefore in the study, fuzzy approach is proposed as an alternative to solve the multi response surface problems. The main aim of this study is to represent the applicability of the fuzzy approach for solving of the multi-response problems in which the probability distributions of the response variables cannot be determined. At the modeling stage, the fuzzy least squares regression analysis, based on Diamond's distance metric, is used. In the optimization stage, the problem is considered as a fuzzy multi-objective optimization problem. Nondominated Sorting Genetic Algorithm-II (NSGA-II), defined in the literature, is adapted by using centroid index fuzzy ranking approach then called Fuzzy NSGA-II (FNSGA-II). Fuzzy Pareto solution set is obtained by optimizing the problem, which is composed of fuzzy objective functions, with FNSGA-II. The proposed fuzzy solution approaches are applied on a data set defined in the literature. Thus, it is seen that an obtained fuzzy Pareto solution is a set of acceptable different response values for the performed multi-response experiments at the defined levels of input variables.
Keywords
References
- Abdullah, L. ve Jamal, N.J. (2010). Centroid- Point of Ranking Fuzzy Numbers and Its Application to Health Related Quality of Life Indicators. International Journal on Computer Science and Engineering (IJCSE) 2(8), 2773-2777.
- Alvarez, M.J., Ilzarbe, L., Viles, E. ve Tanco, M. (2009). The Use of Genetic Algo- rithms in Response Surface Methodology. Quality Technology and Quantitative Management 6(3), 295-307.
- Bashiri, M., Kazemzadeh, R.B., Atkinson, A.C. ve Karimi, H. (2011). Metaheuristic Based Multiple Response Process Opti- mization. Journal of Industrial Engineer- ing, Special Issue 13-23.
- Bashiri, M. ve Hosseininezhad, S.J. (2009). A Fuzzy Programming for Optimizing Multi Response Surface in Robust Designs. Journal of Uncertain Systems 3(3), 163- 173.
- Bashiri, M. ve Ramezani, M. (2010). An interac- tive fuzzy group decision making ap- proach to multiple response problems considering least significant difference. International Journal of Management Science and Engineering Management 5(4), 243-251.
- Bera, S. ve Mukherjee, I. (2010). Performance Analysis of Nelder Mead and A Hybrid Simulated Annealing for Multiple Re- sponse Quality Characteristic Optimiza- tion. Proceedings of the International Multi Conference of Engineers and Com- puter Scientist, Vol III, IMECS, 1728- 1732, Hong Kong.
- Box, G.E.P. and Draper, N.R. (2007). Response Surface Mixtures and Ridge Analysis. John Wiley and Sons, New Jersey.
- Cheng, C.B., Cheng, C.J. ve Lee, E.S. (2002). Neuro-Fuzzy and Genetic Algorithm in Multiple Response Optimization. Com- puters and Mathematics with Applications 44, 1503-1514.
Details
Primary Language
English
Subjects
-
Journal Section
-
Publication Date
August 24, 2012
Submission Date
August 24, 2012
Acceptance Date
-
Published in Issue
Year 2012 Volume: 13 Number: 1
APA
Türkşen, Ö., & Apaydın, A. (2012). MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering, 13(1), 65-79. https://izlik.org/JA36YL72RB
AMA
1.Türkşen Ö, Apaydın A. MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH. AUJST-A. 2012;13(1):65-79. https://izlik.org/JA36YL72RB
Chicago
Türkşen, Özlem, and Ayşen Apaydın. 2012. “MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH”. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 13 (1): 65-79. https://izlik.org/JA36YL72RB.
EndNote
Türkşen Ö, Apaydın A (August 1, 2012) MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 13 1 65–79.
IEEE
[1]Ö. Türkşen and A. Apaydın, “MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH”, AUJST-A, vol. 13, no. 1, pp. 65–79, Aug. 2012, [Online]. Available: https://izlik.org/JA36YL72RB
ISNAD
Türkşen, Özlem - Apaydın, Ayşen. “MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH”. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 13/1 (August 1, 2012): 65-79. https://izlik.org/JA36YL72RB.
JAMA
1.Türkşen Ö, Apaydın A. MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH. AUJST-A. 2012;13:65–79.
MLA
Türkşen, Özlem, and Ayşen Apaydın. “MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH”. Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering, vol. 13, no. 1, Aug. 2012, pp. 65-79, https://izlik.org/JA36YL72RB.
Vancouver
1.Özlem Türkşen, Ayşen Apaydın. MODELING AND OPTIMIZATION OF MULTI-RESPONSE SURFACE PROBLEMS WITH FUZZY APPROACH. AUJST-A [Internet]. 2012 Aug. 1;13(1):65-79. Available from: https://izlik.org/JA36YL72RB