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Title : A Framework for Capturing Uncertainty of Group Decision-Making in the Context of the AHP/ANP
Author(s) : Lanndon Ocampo, Eppie Clark
Author affiliation : 1 Department of Industrial Engineering, De La Salle University, 2401 Taft Avenue, 1004 Manila, Philippines
2 Department of Mechanical Engineering, University of San Carlos, Cebu City, 6000 Cebu, Philippines
Corresponding author img Corresponding author at : Corresponding author img  

Addressing uncertainty in the framework of the analytic hierarchy process (AHP) and its general form, the analytic network process (ANP), has been a dynamic field of research for the last four to five decades. Two directions of research emerged in this domain: the simulation approach and the fuzzy set theory (FST) approach. In this paper, we propose the integration of these two approaches in the context of AHP/ANP to elucidate group decision-making problems. FST is used to handle impreciseness of judgments of individual decision-maker while simulation is used to capture uncertainty brought about by the variability and randomness in aggregating decision-makers’ judgments. These processes are applied at the level of the pairwise comparisons matrices in order to maintain the integrity of the general methodology of the AHP/ANP. The contribution of this work is on developing a methodology that addresses uncertainty both in individual and in group decision-making. The general framework and the detailed methodology are presented in this work. A simple case is used to show the computations.

Key words:Analytic network process; Fuzzy set theory; Simulation; Uncertainty

Cite it:
Lanndon Ocampo, Eppie Clark, A Framework for Capturing Uncertainty of Group Decision-Making in the Context of the AHP/ANP, Advances in Industrial Engineering and Management, Vol.3, No.3, 2014, pp.7-16, doi: 10.7508/AIEM-V3-N3-7-16

Full Text : PDF(size: 396.67 kB, pp.7-16, Download times:374)

DOI : 10.7508/AIEM-V3-N3-7-16

[1] T. L. Saaty, 1980. The Analytic Hierarchy Process, McGraw-Hill: New York.
[2] M. Herva, E. Roca, 2013. Review of combined approaches and multi-criteria analysis for corporate environmental evaluation, Journal of Cleaner Production, vol. 39, pp. 355-371.
[3] A. Gupta, R. Vangari, A.D. Jayal and I.S. Jawahir, 2011. Priority evaluation of product metrics for sustainable manufacturing, In: A. Bernard, editor. Global Product Development, Springer-Verlag Berlin Heidelberg, pp. 631-641.
[4] D. Krajnc and P. Glavic, 2005. A model for integrated assessment of sustainable development, Resources, Conservation and Recycling, vol. 43, no. 2, pp. 189-208.
[5] I.H. Garbie, 2011. Framework of manufacturing enterprises sustainability incorporating globalization issues, In: Proceedings of the 41st International Conference on Computers and Industrial Engineering, Los Angeles, CA USA.
[6] K. de Brucker, C. Macharis and A. Verbeke, 2013. Multi-criteria analysis and the resolution of sustainable development dilemmas: a stakeholder management approach, European Journal of Operational Research, vol. 224, no. 1, pp. 122-131.
[7] S.B. Sirikrai and J.C.S. Tang, 2006. Industrial competitiveness analysis: using the analytic hierarchy process, Journal of High Technology Management Research, vol. 17, no. 1, pp. 71-83.
[8] A. Chatzimouratidis and P. Pilavachi, 2009. Technological, economic and sustainability evaluation of power plants using the Analytic Hierarchy Process, Energy Policy, vol. 37, no. 3, pp. 778-787.
[9] M.S. Chiacchio, 2011. Early impact assessment for sustainable development of enabling technologies, Total Quality Management and Excellence, vol. 39, no. 3, pp. 1-6.
[10] T.J. Barker and Z.B. Zabinsky, 2011. A multicriteria decision-making model for reverse logistics using analytical hierarchy process, Omega, vol. 39, no. 5, pp. 558-573.
[11] S. Seuring, 2013. A review of modeling approaches for sustainable supply chain management, Decision Support Systems, vol. 54, no. 4, pp. 1513-1520.
[12] N. Subramanian and R. Ramanathan, 2012. A review of applications of analytic hierarchy process in operations management, International Journal of Production Economics, vol. 138, no. 2, pp. 215-241.
[13] T.L. Saaty, 2001. Decision making with dependence and feedback: The Analytic Network Process, second ed., RWS Publications: Pittsburg, USA.
[14] D. Paulson and S. Zahir, 1995. Consequences of uncertainty in the analytic hierarchy process: A simulation approach, European Journal of Operational Research, vol. 87, no. 1, pp. 45-56.
[15] D. Hauser and P. Tadikamalla, 1996. The analytic hierarchy process in an uncertain environment: a simulation approach, European Journal of Operational Research, vol. 91, no. 1, pp. 27-37.
[16] T.L. Saaty, 1978. Modeling unstructured decision problems – the theory of analytic hierarchies, Mathematics and Computers in Simulation, vol. 20, no. 3, pp. 147-158.
[17] F. Zahedi, 1986. Group consensus function estimation when preferences are uncertain, Operations Research, vol. 34, no. 6, pp. 883-894.
[18] L.G. Vargas, 1982. Reciprocal matrices with random coefficients, Mathematical Modelling, vol. 3, no. 1, pp. 69-81.
[19] T.L. Saaty and L.G. Vargas, 1987. Uncertainty and rank order in the analytic hierarchy process, European Journal of Operational Research, vol. 32, no. 1, pp. 107-117.
[20] J.M. Moreno-Jimenez and L.G. Vargas, 1993. A probabilistic study of preference structures in the analytic hierarchy process with interval judgments, Mathematical and Computer Modelling, vol. 17, no. 4-5, pp. 73-81.
[21] M.S. Zahir, 1991. Incorporating the uncertainty of decision judgments in the analytic hierarchy process, European Journal of Operational Research, vol. 53, no. 2, pp. 206-216.
[22] A. Arbel and L.G. Vargas, 1993. Preference simulation and preference programming: robustness issues in priority derivation, European Journal of Operational Research, vol. 69, no. 2, pp. 200-209.
[23] B.S. Ahn, 2000. The analytic hierarchy process in an uncertain environment: A simulation approach by Hauser and Tadikamalla (1996), European Journal of Operational Research, vol. 124, no. 1, pp. 217-218.
[24] P.J.M. Van Laarhoven and W. Pedrycz, 1983. A fuzzy extension of Saaty’s priority theory, Fuzzy Sets and Systems, vol. 11, no. 1-3, pp. 199–227.
[25] C. Boender, J.G. deGraan and F.A. Lootsma, 1989. Multi-criteria decision analysis with fuzzy pairwise comparisons, Fuzzy Sets and Systems, vol. 29, no. 2, pp. 133–143.
[26] J.J. Buckley, 1985. Fuzzy hierarchical analysis, Fuzzy Sets and Systems, vol. 17, no. 3, pp. 233–247.
[27] D. Y. Chang, 1996. Application of the extent analysis method on fuzzy AHP, European Journal of Operational Research, vol. 95, no. 3, pp. 649–655.
[28] R. Xu, 2000. Fuzzy least-squares priority method in the analytic hierarchy process, Fuzzy Sets and Systems, vol. 112, no. 3, pp. 359–404.
[29] L. Mikhailov, 2003. Deriving priorities from fuzzy pairwise comparison judgments, Fuzzy Sets and Systems, vol. 134, no. 3, pp. 365–385.
[30] R. Csutora and J.J. Buckley, 2001. Fuzzy hierarchical analysis: the Lambda-Max method, Fuzzy Sets and Systems, vol. 120, no. 2, pp. 181–195.
[31] M.L. Tseng, L. Divinagracia and R. Divinagracia, 2009. Evaluating firm’s sustainable production indicators in uncertainty, Computers & Industrial Engineering, vol. 57, no. 4, pp. 1393–1403.
[32] Y.M. Wang and K.S. Chin, 2008. A linear goal programming priority method for fuzzy analytic hierarchy process and its applications in new product screening, International Journal of Approximate Reasoning, vol. 49, no. 2, pp. 451-465.
[33] M.L. Tseng, 2010. Implementation and performance evaluation using the fuzzy network balanced scorecard, Computers and Education, vol. 55, no. 1, pp. 188-201.
[34] M.L. Tseng, R.J. Lin, Y.H. Lin, R.H. Chen and K. Tan, 2014. Close-loop or open hierarchical structures in green supply chain management under uncertainty, Expert Systems with Applications, vol. 41, no. 7, pp. 3250–3260.
[35] N.S. Arunraj, S. Mandal and J. Maiti, 2013. Modeling uncertainty in risk assessment: An integrated approach with fuzzy set theory and Monte Carlo simulation, Accident Analysis & Prevention, vol. 55, pp. 242-255.
[36] T.L. Saaty, 2008. The analytic hierarchy and analytic network measurement processes: applications to decisions under risk, European Journal of Pure and Applied Mathematics, vol. 1, no. 1, pp. 122-196.
[37] M.A.B. Promentilla, T. Furuichi, K. Ishii and N. Tanikawa, 2008. A fuzzy analytic network process for multi-criteria evaluation of contaminated site remedial countermeasures, Journal of Environmental Management, vol. 88, no. 3, pp. 479-495.
[38] P.F. Hsu and M.H. Kuo, 2011. Applying the ANP model for selecting the optimal full-service advertising agency, International Journal of Operations Research, vol. 8, no. 4, pp. 48-58.
[39] L.A. Zadeh, 1965. Fuzzy set, Information and Control, vol. 18, no. 3, pp. 338-353.
[40] M.L. Tseng, 2009. A causal and effect decision-making model of service quality expectation using grey-fuzzy DEMATEL approach, Expert Systems with Applications, vol. 36, no. 4, pp. 7738-7748.
[41] R.C. Wang and S.J. Chuu, 2004. Group decision-making using a fuzzy linguistic approach for evaluating the flexibility in a manufacturing system, European Journal of Operational Research, vol. 154, no. 3, pp. 563–572.
[42] C. Von Altrock, 1996. Practical Fuzzy-Logic Design, The Computer Applications Journal, Circuit Cellar INK., vol. 75, pp. 1-5.
[43] U. Asan, C. Erhan Bozdag and S. Polat, 2004. A fuzzy approach to qualitative cross impact analysis, Omega – International Journal of Management Science, vol. 32, no. 6, pp. 443–458.
[44] S. Opricovic and G.H. Tzeng, 2003. Defuzzification within a multi-criteria decision model, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 11, no. 5, pp. 635–652.
[45] M.L. Tseng, 2011. Green supply chain management with linguistic preferences and incomplete information, Applied Soft Computing, vol. 11, no. 8, pp. 4894-4903.
[46] M.L. Tseng and A.S.F. Chiu, 2013. Evaluating firm’s green supply chain management in linguistic preference, Journal of Cleaner Production, vol. 40, no. 22-31.
[47] M.L. Tseng, Y.H. Lin, A.S.F. Chiu and J.C.H. Liao, 2008. Using FANP approach on selection of competitive priorities based on cleaner production implementation: a case study in PCB manufacturer, Taiwan, Clean Technologies and Environmental Policy, vol. 10, no. 1, pp. 17-29.

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