During the past two decades, there have been tremendous efforts on developing efficient business excellence models to improve the quality of organizations. A typical business excellence model proposes several alternatives with different budget and the primary objective is to use the best ones. In this paper, we present a robust LINMAP method for measuring the relative importance of various alternatives in an EFQM self assessment. The presented robust model is capable of handling uncertainty as part of the problem formulation. The proposed model of this paper is implemented for a case-study of energy sector in Iran with various alternatives. The orderings of the alternatives are measured using data from multiple experts through applying the proposed model of this paper.

Gharakhani, M., Rasouli, S & Babakhani, M. (2011). A robust LINMAP for EFQM self assessment.Management Science Letters, 1(2), 213-222.

Ben-Tal, A., & Nemirovski, A. (2000). Robust solutions of linear programming problems contaminated with uncertain data. Mathematical Programming, 88, 411- 421.

Bertsimas, D., & Sim, M. (2003). Robust discrete optimization and network flows, Mathematical Programming Series B, 98, 49-71.

Carlsson, C., & Fuller, R. (2000). Multiobjective linguistic optimization. Fuzzy Sets and Systems, 115, 5–10.

Chen, S. M., & Tan, J. M. (1994). Handling multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets and Systems, 67, 163–172.

Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114, 1–9.

Delgado, M., Verdegay, J. L., & Vila, M. A. (1992). Linguistic decision-making models. International Journal of Intelligent System, 7, 479–492.

Fisher, B. (2003). Fuzzy environmental decision-making: applications to air pollution. Atmospheric Environment,37, 1865–1877.

Gharakhani, M., Taghipour, T., & Jalali Farahani, K. (2010). A robust multi-objective production planning. International Journal of Industrial Engineering Computations, 1(1), 73-78.

Hong, D., & Choi, C. (2000). Multicriteria fuzzy decision-making problems based on vague set theory, Fuzzy sets and systems, 114(1), 103-113.

Hwang, C. L., & Yoon, K. (1981). Multiple attributes decision making methods and applications. Springer: Berlin Heidelberg.

Li, D.-F. (2005a). An approach to fuzzy multiattribute decision making under uncertainty. Information Sciences, 169, 97–112.

Li, D.-F. (2005b).Multiattribute decision making models and methods using intuitionistic fuzzy sets. Journal of Computer and System Sciences, 70, 73–85.

Li, D.-F. (2004). Some measures of dissimilarity in intuitionistic fuzzy structures. Journal of Computer and System Sciences, 68, 115–122.

Li, L., Yuan, X-H., & Xia, Z-Q. (2007). Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets. Journal of Computer and System Sciences, 73, 84–88.

Liu, H.-W., & Wang, G.-J. (2007). Multi-criteria decision-making methods based on intuitionistic fuzzy sets. European Journal of Operational Research, 179, 220–233.

Sadjadi, S.J., & Omrani, H. (2008). Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies. Energy Policy, 36, 4247– 4254.

Sadjadi, S. J., & Omrani, H. (2009). A bootstrapped robust data envelopment analysis model for efficiency estimating of telecommunication companies in Iran. Telecommunication Policy, 34(4), 221-232.

Soyster, A. L. (1973). Convex programming with eet-inclusive constraints and applications to inexact linear programming. Operations Research, 21, 1154-1157.

Srinivasan, V., & Shocker, A. D. (1973). Linear programming techniques for multidimensional analysis of preference. Psychometrica, 38, 337–342.

Wang, J., & Lin, Y.-I. (2003). A fuzzy multicriteria group decision making approach to select configuration items for software development. Fuzzy Sets and Systems, 134, 343–363.

Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–356.