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The VIKOR method was developed for multi-criteria optimization of complex systems. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria. It introduces the multi-criteria ranking index based on the particular measure of “closeness” to the “ideal” solution. The aim of this paper is to extend the VIKOR method for decision making problems with ratings of alternatives being expressed using intuitionistic fuzzy sets and criteria weights is completely unknown. To determine the weights with respect to a set of criteria represented by intuitionistic fuzzy sets, we establish an entropy weight model, which can be used to get the criteria weights. Furthermore, a novel nonlinear normalization technique is adapted to modify the VIKOR. Finally, a compared numerical example illustrates and clarifies the main results developed in this paper.