Abstract—Most of the studies in Response Surface Methodology commonly involve one response or quality characteristics, whereas in most industrial applications considering all responses simultaneously is required. Multiple Response Surface (MRS) Optimization Problems often deal with responses that are conflicting. In dealing with incommensurate responses, incorporating a decision maker’s preference information into the problem has lots of advantages although a few researches in MRS literature has taken this into attention. This paper tends to take a detailed look at the most prominent approaches that has been suggested so far in MRS, also review and discuss the classifications with a special focus on the decision maker’s preference information. In today’s competitive market satisfying the customer is of high importance. The DM can be a customer and reaching a compromise with an interactive method would help the firm to succeed in having loyal customers. Results of the case study shows that applying a meta-heuristic algorithm with existing MRS approaches lead to better findings .finally future areas for research are discussed.
Index Terms—multiple response surface optimization; response surface methodology; decision maker; design of experiments.
Amineh Zadbood. is a Master Student in Iran University of science and technology, Department of Industrial Engineering, Tehran, Iran (corresponding author to provide phone: 98912-593-7642; e-mail: zadbood85@ gmail.com).
Kazem Noghondarian, is an Assistant Professor in Iran University of science and technology, Department of Industrial Engineering, Tehran, Iran (e-mail: firstname.lastname@example.org).
Cite: Amineh Zadbood and Kazem Noghondarian, "Considering Preference Parameters in Multi Response Surface Optimization Approaches," International Journal of Modeling and Optimization vol. 1, no. 2, pp. 158-162, 2011.