Ranking Multi Criteria Decision Making Methods for a Problem by Area Under Receiver Operating Characteristic
Journal of Investment and Management
Volume 4, Issue 5, October 2015, Pages: 210-215
Received: Jul. 20, 2015;
Accepted: Aug. 3, 2015;
Published: Aug. 13, 2015
Views 3958 Downloads 134
Seyed Behnam Khakbaz, Faculty of Management, University of Tehran, Tehran, Iran
Maryam Karimi Davijani, College of Farabi, University of Tehran, Qom, Iran
One of the major challenges in decision making is selection among MCDM (multi criteria decision making) methods. These methods do not provide same answer to decision maker. Therefore selecting the best answer is an important dilemma. To solve this problem, methods like Borda and Copeland compilation have been proposed. However, applying these methods leads to a hybrid solution which is not necessarily the best answer. In this paper a new approach is proposed to rank different MCDM methods. This approach is AUROC (area under receiver operating characteristic) which is a data mining tool for ranking classification models. The results would show great potential of applying AUROC for ranking MCDM methods in an immense selection problem with historical outcome
Seyed Behnam Khakbaz,
Maryam Karimi Davijani,
Ranking Multi Criteria Decision Making Methods for a Problem by Area Under Receiver Operating Characteristic, Journal of Investment and Management.
Vol. 4, No. 5,
2015, pp. 210-215.
A. Salo, T. Gutafsson and R. Ramanathan, "Multicriteria methods for technology foresight," Jurnal of Forcasting, pp. 235-255, 2003.
A. Guitouni and J.-M. Martel, "Tentative guidelines to help choosing an appropriate MCDA method," European Journal of Operational Research, pp. 501-521, 1998.
S. H. Zanakis, A. Solomon, N. Wishart and S. Dublish, "Multi-attribute decision making: A simulation comparison of select methods," European Journal of Operational Research, pp. 507-529, 1998.
V. M. Athawale and S. Chakraborty, "A comparative study on the ranking performance of some multi-criteria decision-making methods for industrial robot selection," International Journal of Industrial Engineering Computations, pp. 831-850, 2011.
E. Triantaphyllou, B. Shu, S. Nieto Sanchez and T. Ray, "Multi-Criteria Decision Making: An Operations Research Approach," Encyclopedia of Electrical and Electronics Engineering, pp. 176-186, 1998.
M.-. T. Chu, J. Shyu, G.-. H. Tzeng and R. Khosla, "Comparison among three analytical methods for knowledge communities group-decision analysis," Expert Systems with Applications, pp. 1011-1024, 2007.
S. Opricovic and G.-. H. Tzeng, "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, pp. 445-455, 2004.
J. Antucheviciene, A. Zakarevicius and E. K. Zavadskas, "Measuring Congruence of Ranking Results Applying Particular MCDM Methods," INFORMATICA, pp. 319-338, 2011.
I. H. Witten and E. Frank, Data Mining Practical Macine Learning Tools and Techniques, San Francisco: Morgan Kaufmann, 2005.
H. Jiawei, M. Kamber and J. Pei, Data Mining Concepts and Techniques, Waltham: Morgan Kaufmann, 2012.
Clementine® 12.0 Algorithms Guide, Chicago: Integral Solutions Limited, 2007.
J. C. Harsanyi, "Cardinal welfare, individualistic ethics, and interpersonal comparisons of utility," Journal of Political Economy, pp. 309-321, 1955.
R. B. R. a. N. S. Benayoun, "Manual de reference du programme electre, Note de Synthese et Formation," Direction Scientifique SEMA, 1966.
F. T. M. a. F. V. Lootsma, "Multi-criteria analysis and budget reallocation in long-term research planning," European Journal of Operational Research, pp. 293-305, 1990.
C. L. Hwang and K. Yoon, Multiple Attribute Decision Making: Methods and application, New York: Springer- Verlag, 1981.
K. Yoon, "A reconcilation among discrete compromise situation," Journal of Operational Research Society, pp. 277-286, 1987.
C. L. Hwang, Y. J. Lai and T. Y. Liu, "A new approach for multiple objective decision making," Computers and Operational Research, pp. 889-899, 1993.
M. F. El-Santawy, "A VIKOR Method for Solving Personnel Training Selection Problem," INTERNATIONAL JOURNAL OF COMPUTING SCIENCE, pp. 9-12, 2012.