Volume 3 Issue 3 pp. 463-476 Spring, 2012


Evaluating high risks in large-scale projects using an extended VIKOR method under a fuzzy environment


S. Ebrahimnejad, S. M. Mousavi, R Tavakkoli-Moghaddam and M Heydar


The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM) methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment.


DOI: 10.5267/j.ijiec.2011.12.001

Keywords: Risk evaluation, Large-scale projects, Fuzzy sets, VIKOR

References

References Al-Subhi Al-Harbi, K.M. (2001). Application of the AHP in project management, International Journal of Project Managements, 19, 19-27.

Büyüközkan, G., & Ruan, D. (2008). Evaluation of software development projects using a fuzzy multi-criteria decision approach, Mathematics and Computers in Simulation, 77, 464–475.

Chen, L.Y., & Wang, T.-C. (2009). Optimizing partners’ choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR, International Journal of Production Economics, 120, 233-242.

Chin, K., Xu, D., Yang, J., & Lam, J. (2008). Group-based ER-AHP system for product project screening, Expert System with Application, 35(4). 1909–1929.

Dey, P.K. (2002). Project risk management: a combined analytic hierarchy process and decision tree analysis approach, Cost Engineering Journal, 44 (3). 13–26.

Dey, P.K., & Ogunlana, S.O. (2004). Selection and application of risk management tools and techniques for build-operate-transfer project, Industrial Management and Data System, 104(4). 334–346.

Dey, P.K., Tabucanon, M.T., & Ogunlana, S.O. (1994). Planning for project control through risk analysis; a case of petroleum pipeline laying project, International Journal of Project Management, 12(1). 23–33.

Ebrahimnejad, S., Mousavi, S.M., & Mojtahedi, S.M.H. (2008). A model for risk evaluation in construction projects based on fuzzy MADM, In: Proceeding of the 4th IEEE International Conferences on Management of Innovation & Technology, Thailand, 305-310.

Ebrahimnejad, S., Mousavi, S.M., & Mojtahedi, S.M.H. (2009). A fuzzy decision making model for risk ranking with application to the onshore gas refinery, International Journal of Business Continuity and Risk Management, 1, 38-66.

Ebrahimnejad, S., Mousavi, S.M., & Seyrafianpour, H. (2010). Risk identification and assessment for build–operate–transfer projects: A fuzzy multi attribute decision making model, Expert System with Application, 37, 575–586.

Kahraman, C., Büyüközkan, G., & Yasin Ates, N. (2007). A two phase multi-attribute decision-making approach for new product introduction, Information Sciences, 177, 1567–1582.

Kaufmann, A., & Gupta, M.M. (1985). Introduction to fuzzy arithmetic: theory and applications, Van Nostrand Reinhold, New York.

Kumar Dey, P. (2010). Managing project risk using combined analytic hierarchy process and risk map, Applied Soft Computing, 10, 990-1000.

Li, D., & Yang, J.B. (2004). Fuzzy linear programming technique for multi-attribute group decision making in fuzzy environments, Information Sciences, 158, 263–275.

Makui, A., Mojtahedi, S.M.H., & Mousavi, S.M. (2010). Project risk identification and analysis based on group decision making methodology in a fuzzy environment, International Journal of Management Science and Engineering Management, 5(2). 108-118.

Mojtahedi, S.M.H., Mousavi, S.M., & Makui, A. (2010). Project risk identification and assessment simultaneously using multi-attribute group decision making technique, Safety Science, 48(4). 499-507.

Mousavi, S.M., Tavakkoli-Moghaddam, R., Azaron, A., Mojtahedi, S.M.H., & Hashemi, H. (2011). Risk assessment for highway projects using jackknife technique, Expert Systems With Applications, 38, 5514–5524.

Mousavi, S.M., Tavakkoli-Moghaddam, R., Hashemi, H., & Mojtahedi, S.M.H. (2011b). A novel approach based on non-parametric resampling with the interval analysis for large engineering project risks. Safety Science, 49(10), 1340-1348.

Mustafa, M.A., & Al-Bahar, J.F. (1991). Project risk assessment using the analytic hierarchy process, IEEE Transactions on Engineering Management, 38(1). 46–52.

Nieto-Morote, A., & Ruz-Vila, F. (2011). A fuzzy approach to construction project risk assessment, International Journal of Project Management, 29, 220-231.

Opricovic, S. (1998). Multicriteria optimization of civil engineering systems, Faculty of Civil Engineering, Belgrade.

Opricovic, S., & Tzeng, G.-H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156, 445–455.

Opricovic, S., & Tzeng, G.-H. (2007). Extended VIKOR method in comparison with outranking methods, European Journal of Operational Research, 178, 514–529.

PMI. (2008). A guide to the project management body of knowledge (PMBOK Guide). 4th ed., USA, Project Management Institute Inc., Chapter 11 on project risk management.

Tavakkoli-Moghaddam, R., Mousavi, S.M., & Hashemi, H. (2011). A fuzzy comprehensive approach for risk identification and prioritization simultaneously in EPC projects, InTech Publisher, Published in the book "Risk Management / Book 2", ISBN 978-953-307-482-5.

Tavakkoli-Moghaddam, R., Mousavi, S.M., & Heydar, M. (2011). An integrated AHP-VIKOR methodology for plant location selection, International Journal of Engineering, Article in press.

Tsuar, S.H., Chang, T.Y., & Yen, C.H. (2002). Evaluation of airline service quality by fuzzy MCDM, Tourism Management, 23, 107–115.

Wang, T.-C., & Chang, T.-H. (2007). Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment, Expert System with Application, 33, 870–880.

Wu, H.-Y., Tzeng, G.-H., & Chen, Y.-H. (2009). A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard, Expert System with Application, 36, 10135-10147.

Xia, H.C., Li, D.F., Zhou, J.Y., & Wang, J.M. (2006). Fuzzy LINMAP method for multi attribute decision making under fuzzy environments, Journal of Computer and System Sciences, 72, 741–759.

Zayed, T., Amer, M., & Pan, J. (2008). Assessing risk and uncertainty inherent in Chinese highway projects using AHP, International Journal of Project Management, 26, 406–419.

Zeng, J., An, M., & Smith, N.J. (2007). Application of a fuzzy based decision making methodology to construction project risk assessment, International Journal of Project Management, 25, 589–600.

Zimmermann, H.J. (1991). Fuzzy set theory and its applications, 2nd ed., Boston, Dordrecht, London: Kluwer Academic Publishers.