Reversible decision support system: Minimising cognitive dissonance in multi-criteria based complex system using fuzzy analytic hierarchy process

In a multi-criteria system, it is often required to optimize the decision according to the given problem set. In this paper, a reversible decision support system has been utilized in a human-machine system to select the best decision among the selected alternatives. A reversible decision support system is used to interchange the alternatives between inputs and outputs. It also examines the dissonance level while taking decisions and ranked alternatives according to the attributes and sub-attributes of each criterion. These decisions have been classified into two segments such as reversible and irreversible. This paper highlights the reversible aspects of the alternatives and how it can be performed better with minimum dissonance. Fuzzy analytic hierarchy process has been applied especially triangular membership function to evaluate interim judgments. Triangular fuzzy number is implemented to form the perception of alternatives with different weights for each factor and sub-factor. Moreover, this study reveals that cognitive dissonance can be reduced in a reversible environment to resolve multi-constraint. Finally, performance of the proposed reversible decision support system has been analysed through an experiment to demonstrate its merits and capabilities. The result shows that the final decision has less dissonance level and more satisfaction when users get the chance to reverse the decision.