Strategy selection by using interval type-2 fuzzy mcdm and an application

  • Yavuz Selim Özdemir University of Turkish Aeronautical Association
  • Ali Üsküdar
Keywords: balanced score card, group decision-making, interval type-2 fuzzy AHP, interval type-2 fuzzy TOPSIS, strategy selection

Abstract

Competitive market conditions today are becoming more challenging in every sector. Companies must determine their road maps in terms of short, mid and long-term strategies. The selection of the most suitable strategy by a group of decision makers is a very complicated process. As the same linguistic expression can represent different meanings to different people the fuzzy decision-making process is a good tool to use in group decisions. Various methods and different linguistic terms are used to define fuzzy sets. In recent years, the interval type-2 fuzzy AHP and interval type-2 TOPSIS methods have been introduced in the literature, as well as the type-1 fuzzy AHP and type-1 fuzzy TOPSIS methods. The aim of this study is to present a new model for group decision-making with the Balanced Score Card, fuzzy AHP and fuzzy TOPSIS methods by using interval type-2 fuzzy sets. The proposed model was applied in the strategy selection process of a large-scale public transportation company that operates in Istanbul/Turkey.

Author Biography

Yavuz Selim Özdemir, University of Turkish Aeronautical Association
Asst. Prof. Dr. Yavuz Selim ÖZDEMİRVice-Chairman of Industrial Engineering Department
Faculty of Engineering
University of Turkish Aeronautical AssociationAnkara, Turkey

References

Abdullah, L., & Najib, L., 2014. A new type-2 fuzzy set of linguistic variables for the fuzzy analytic hierarchy process. Expert Systems with Applications, 41(7), 3297–3305.

Akdag, H., Kalaycı, T., Karagöz, S., Zülfikar, H., & Giz, D., 2014. The evaluation of hospital service quality by fuzzy MCDM. Applied Soft Computing, 23, 239–248.

Chen, S.-M., & Lee, L.-W., 2010a. Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Expert Systems with Applications, 37(4), 2790–2798.

Chen, S. M., & Lee, L. W., 2010b. Fuzzy multiple attributes group decision-making based on the ranking values and the arithmetic operations of interval type-2 fuzzy sets. Expert Systems with Applications, 37(1), 824–833.

Chen, S. M., Yang, M. W., Lee, L. W., & Yang, S. W., 2012. Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets. Expert Systems with Applications, 39(5), 5295–5308.

Chiao, K.-P., 2012. Trapezoidal interval type-2 fuzzy set extension of Analytic Hierarchy Process. 2012 IEEE International Conference on Fuzzy Systems, 1–8.

Erdoğan, M., & Kaya, İ., 2014. A type-2 fuzzy MCDM method for ranking private universities in İstanbul. In Proceedings of the World Congress on Engineering, 1, 2-4.

Hwang, C.-L., & Yoon, K., 1981. Methods for Multiple Attribute Decision Making. Multiple Attribute Decision Making: Methods and Applications. 58–191.

Kahraman, C., Onar, S. C., & Oztaysi, B., 2015. Fuzzy Multicriteria Decision-Making: A Literature Review. International Journal of Computational Intelligence Systems, 8(4):637-666

Kahraman, C., & Öztayşi, B., 2013. Personnel selectıon usıng type -2 fuzzy ahp method. The Business & Management Review, 4(1), 118–126.

Kahraman, C., Öztayşi, B., Uçal Sarı, İ., & Turanoğlu, E., 2014. Fuzzy analytic hierarchy process with interval type-2 fuzzy sets. Knowledge-Based Systems, 59, 48–57.

Kaplan, R. S., 2009. Conceptual Foundations of the Balanced Scorecard. Handbooks of Management Accounting Research, 3, 1253–1269.

Kaplan, R. S., & Norton, D., 1992. The balanced score card measures that drive performance. Harvard Business Review, 70(1), 71–79.

Kelemenis, A., & Askounis, D., 2010. A new TOPSIS-based multi-criteria approach to personnel selection. Expert Systems with Applications, 37(7), 4999–5008.

Lee, A. H. I., Chen, W. C., & Chang, C. J., 2008. A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Systems with Applications, 34(1), 96–107.

Mardani, A., Jusoh, A., & Zavadskas, E. K., 2015. Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014. Expert Systems with Applications, 42(8), 4126–4148.

Mendel, J. M., & Wu, H., 2006. Type-2 fuzzistics for symmetric interval type-2 fuzzy sets: Part 1, forward problems. IEEE Transactions on Fuzzy Systems, 14(6), 781–792.

Özek, M. B., 2010. A New Approach For Fuzzy Logic: Type-2 Fuzzy Logic. Engineering Sciences, 5(3), 541-557.

Saaty, T. L., 1980. The Analytic Hierarchy Process. Education, 1–11.

Vahdani, B., Zandieh, M., & Tavakkoli-Moghaddam, R., 2011. Two novel FMCDM methods for alternative-fuel buses selection. Applied Mathematical Modelling, 35(3), 1396–1412.

Zadeh, L. A., 1975. The concept of a linguistic variable and its application to approximate reasoning-I. Information Sciences, 8(3), 199–249.

Zadeh, Lotfi A., 1965. Fuzzy Sets. Information and Control, 8(3), 338–353.

Zamri, N., & Abdullah, L., 2013. A new linguistic variable in interval type-2 fuzzy entropy weight of a decision making method. In Procedia Computer Science, 24, 42–53.

Published
2020-08-13
Section
Industrial Engineering