Volume 1 Issue 2 pp. 173-184 July, 2010


Fuzzy analytical hierarchy process using preference ratio: A case study for selecting management short course in a business school


Mohammad Modarres, Soheil Sadi-Nezhad and Farzane Arabi


Analytic Hierarchy Process (AHP) is one of the most popular approaches in the area of multiple attribute decision making (MADM). However, it is not practical any more if input information are fuzzy. In this paper, we propose a new method for fuzzy AHP which is especially useful to make decisions for multiple attribute problems. The method is developed by applying preference ratio concept which makes it practical since it assigns crisp weights and crisp scores to different alternatives. Two algorithms are proposed in this paper: The first one defines crisp and normalized weight by pairwise comparison with fuzzy data while the second one calculates fuzzy consistency ratio. The proposed method is applied to prioritize different short courses in a management school.


DOI: 10.5267/j.ijiec.2010.02.006

Keywords: FAHP, Preference ratio, MADM, Fuzzy numbers, Consistency ratio, AHP
References

Buckley, J. (1985). Fuzzy Hierarchical Analysis. Fuzzy Sets and Systems, 17(3), 233-247.

Buckley.J, Feuring.T & Hayashi. Y.(2001). Fuzzy hierarchical analysis revisited. European Journal of Operational Research, 129, 48-64.

Chang, P-L., & Chen, Y-C.(1994). A Fuzzy multi – criteria decision making method for technology transfer strategy selection in bio technology. Fuzzy Sets and Systems, 64, 131-139.

Chang, D.Y. (1996). Application of the extent analysis method on fuzzy AHP. European Journal of Operational Research,116, 649 – 655.

Chen, S. J. & C. L. Hwang (1992)., Fuzzy Multiple Attribute Decision Making. Springer-Verlag,

Cheng, C.H. (1996). Evaluating Naval tactical Missile Systems by Fuzzy AHP based on the Grade Value of Membership function. European Journal of Operational Research, 96, 343-350.

Cheng, C-H, Yang, K-L & Hwang, C-L. (1999). Evaluating attack helicopter by AHP based on linguistic variable. European Journal Operational Research, 423 – 435.

Deng, Y. & Chang, Y-H. (2000). Fuzzy multi criteria analysis for performance evaluation of bus companies. European Journal of Operational Research, 126, 459-473.

Huang, C-C., Chu, P-Y. & Chiang, Y-H. (2008). A fuzzy AHP application in government-sponsored R&D project selection. Omega, 36 (6), 1038-1052.

Huang, L-C. & Wu, R. (2005). Applying fuzzy analytic hierarchy process in the managerial talent assessment model – an empirical study in Taiwan's semiconductor industry. International Journal of Technology Management, 30(1-2), 105-130.

Laarhoven, P.J.M., & W.Pedrycz. (1985). A Fuzzy Extension of Saaty’s Priority Theory. Fuzzy Sets and Systems, 11(3), 229 – 241.

Leung, L.C. & Cao., D. (2000). On consistency and ranking of alternatives in fuzzy AHP. European Journal of Operational Research, 126, 459-473.

Lin, H-F., Lee, H-S & Wang, D. W. (2009). Evaluation of factors influencing knowledge sharing based on a fuzzy AHP approach. Journal of Information Science, 35 (1), 25-44.

Mikhailov. L. (2004). A fuzzy approach to driving priorities from interval pair wise comparison judgments. European Journal of Operational Research, 159, 687-704.

Mikhailov. L & Tsvetinov, P. (2004). Evaluation of services using a fuzzy analytic Hierarchy Process. Applied Soft Computing, 5, 23-33.

Modarres. M & Sadi-Nezhad, S. (2001). Ranking fuzzy numbers by preference ratio. Fuzzy Sets and Systems, 118, 429-436.

Modarres, M. & Sadi-Nezhad, S. (2005). Fuzzy simple additive weighting method by preference ratio. Intelligent Automation and Soft Computing. 11, 235-244.

Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15, 234-281.

Saaty,T.L. (2006). Rank from comparisons and from rating in the analytic hierarchy/network. European Journal of Operational Research, 168, 557-570.

Saaty, T. L. & Vargas, L. (1994) Decision making with analytic hierarchy process. RWS.

Saaty,T. L. (1996). The analytic hierarchy process. RWS.

Şen, C. G & Çinar, G. (2010). Evaluation and pre-allocation of operators with multiple skills: A combined fuzzy AHP and max-min approach. Expert Systems with Applications, 37, 2043-2053.

Torfi, F., Farahani, R. Z & Rezapour, S. (2010). Fuzzy AHP to determine the relative weights of evaluation criteria and fuzzy TOPSIS to rank the alternatives. Applied Soft Computing Journal, 10 (2), 520-528.

Yeh ,Deng & Yo- Hern Chang. (2000). Fuzzy multi criteria analysis for performance evaluation of bus companies. European Journal of Operational Research, 126, 459-473

Zhu, K. J., Jing, Y. & Chang, D. Y. (1999). A discussion on Extent Analysis Method and applications of Fuzzy AHP. European Journal of Operational Research, 116, 450-456