The interactivity between the criteria in MCDM problem

Document Type : Research Paper


1 MSc. Student in Industrial Engineering, Dep. of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan, Iran

2 Assistant Prof. of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan, Iran


The purpose of this study is to provide new methods for the problem with criteria interactivity in MCDM problem. Considering that the assessment criteria in MCDM may have effects on each other, so there are the necessary methods that take into account these interactions. This research In addition to identification, study, and Classify the different interaction that may the criteria have, introduces two new ways in this context. The new method presented in this paper is to solve the problems with the interactions between the criteria. The interaction between the criteria to be considered as a set of interactive effects between the criteria. The paper also offered two new ways to solve such problems. The proposed method approach is the effect of the interactions on the decision matrix.


Armstrong, D. J. (2004). Causal Mapping: A Discussion and Demonstration. USA: IGI Global.
Asgharizadeh, E., Haghighi, M., & Balali, M. (2008). A Decision Making Model with AHP for Choosing the Merging, Acquisition and Joint Venture Strategies in Auto Industry. Journal of Industrial Management. 1 (3), 5-20. (in Persian)
Barlas, Y. (2007). System dynamics: systemic feedback modeling for policy analysis. SYSTEM, 1, 59.
Baykasoğlu, A., Kaplanoğlu, V., Durmuşoğlu, Z.D.U. & Şahin, C. (2013). Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection. Expert Systems with Applications, 40(3), 899-907.
Boutilier, C., Bacchus, F. & Brafman, R. I. (2001). UCP-networks: A directed graphical representation of conditional utilities. Paper presented at the Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence.
Boutilier, C., Brafman, R. I., Domshlak, C., Hoos, H. H. & Poole, D. (2004). CP-nets: A tool for representing and reasoning with conditional ceteris paribus preference statements. Journal of Artificial Intelligence Research, 21 (2004), 135–191.
Châtel, P., Truck, I. & Malenfant, J. (2010). LCP-Nets: A Linguistic Approach for Non-functional Preferences in a Semantic SOA Environment. Journal of Universal Computer Science, 16(1), 198-217.
Dubois, D., Marichal, J.-L., Prade, H., Roubens, M., & Sabbadin, R. (2001). The Use Of The Discrete Sugeno Integral In Decision-Making: A Survery. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 9(05), 539-561.
Dyer, J. S. (2005). MAUT—multiattribute utility theory Multiple criteria decision analysis: state of the art surveys (pp. 265-292): Springer.
Fishburn, P. C. (1965). Independence in utility theory with whole product sets. Operations Research, 13(1), 28-45.
Fontela, E. & Gabus, A. (1976). The DEMATEL observer: DEMATEL 1976 report. Switzerland Geneva: Battelle Geneva Research Center.
Ghasemieh, R., Jamali, G., & Karimiasl, E. (2015). Analysis of LARG Supply Chain Management Dimensions in Cement Industry (An Integrated multi-Criteria Decision Making Approach). Journal of Industrial Management, 7(4), 813-836. (in Persian)
Gölcük, İ. & Baykasoğlu, A. (2016). An analysis of DEMATEL approaches for criteria interaction handling within ANP. Expert Systems with Applications, 46, 346-366.
Grabisch, M. & Labreuche, C. (2010). A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid. Annals of Operations Research, 175(1), 247-286.
Huang, J.-J., Tzeng, G.-H. & Ong, C. S. (2005). Multidimensional data in multidimensional scaling using the analytic network process. Pattern Recognition Letters, 26(6), 755-767.
Kahraman, C., Yasin Ates, N., Çevik, S., Gülbay, M., & Ayça Erdogan, S. (2007). Hierarchical fuzzy TOPSIS model for selection among logistics information technologies. Journal of Enterprise Information Management, 20(2), 143-168.
Kosko, B. (1986). Fuzzy cognitive maps. International Journal of man-machine studies, 24(1), 65-75.
Nielsen, T. D. & Jensen, F. V. (2009). Bayesian networks and decision graphs: USA: Springer Science & Business Media.
Pahlavani, A. (2008). Investment Prioritization through Group Decision Making Method of Hierarchical TOPSIS in Fuzzy Environment. Journal of Industrial Management, 2(1), 35-54. (in Persian)
Punniyamoorthy, M., Mathiyalagan, P., & Parthiban, P. (2011). A strategic model using structural equation modeling and fuzzy logic in supplier selection. Expert Systems with Applications, 38(1), 458-474.
Rouhi, F., Ebrahimi, S. B., & Ketabian, H. (2015). Development of International facility location model applying the combination of MCDM and location covering techniques under uncertainty. Journal of Industrial Management, 7(4), 743-766. (in Persian)
Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European journal of operational research, 48(1), 9-26.
Satty, T. L. (1996). Decision making with dependence and feedback: The analytic network process. RWS Publication.