The stratified multi criteria decision making method: An extended version

ABSTRACT

It often occurs that after a multi-criteria decision is made, the decision maker becomes unsure as to whether they have made the best decision. This doubt arises because the criteria being considered do not carry the same weightings. This instability is relevant to the consideration of possible future events, such as a possible recession following the COVID-19 outbreak, which may affect the criteria weightings. The stratified multi-criteria decision-making method (SMCDM) has been proposed to address this issue. This method suggests the consideration of a number of states in the decision-making process. In each state, the weightings of the criteria are different depending on which event or which combination of events are being considered. The states are associated with transition probabilities that are used to compute the optimal weightings of the criteria. This paper suggests approaches to compute the transition probabilities. Moreover, the consideration of several events in SMCDM results in a great number of states and this would be a time consuming and error prone process. Hence, the incremental enlargement characteristic of the concept of stratification (CST) is added to SMCDM in order to reduce the large numbers of states to a manageable quantity. IEEE