An analysis of criteria interaction techniques in multiple attribute decision making and a fuzzy TOPSIS based new model proposal

The aim of this study is to shed light on the concept of criteria independence/dependence and propose a simple and effective method to deal with complex decision problems without the restrictive assumption of preferential independence. For this thought in line, we provide a comprehensive survey of the state of art methodologies used for modelling and solving MCDM problems with interdependent/interactive criteria. Initially, the independence assumptions of the classical decision theory are compiled from the multi attribute utility theory. Then focusing on the preferential independence concept, Analytical Network Process, Causal Maps, Decision-Making Trial and Evaluation Laboratory (DEMATEL), Fuzzy Cognitive Maps, Interpretive Structural Modelling, Bayesian Networks, System Dynamics, and Fuzzy Integral (specifically Choquet Integral) methods are explained and discussed. Literature survey of the pertinent methods is provided at the end of each chapter. Due to the excessive number of alternative methods capable of modelling criteria interactions, characteristics of a sufficient MCDM method are determined as a complexity management strategy. In our regard, Fuzzy Cognitive Maps has much to offer in the field of MCDM due to its capabilities in qualitative modelling and simulating the dynamic systems. We propose a novel hybrid MCDM method by combining Hierarchical Fuzzy TOPSIS and Fuzzy Cognitive Maps for modelling interdependent, complex, and uncertain problems. The proposed method is illustrated in the strategy selection problem to demonstrate practicality and applicability of the method.