Comparative study of MCDM methods under different levels of uncertainty

Often, data in MCDM problems are imprecise and changeable due to the mandatory participation of human judgement, which is often unclear vague. Hence, selection an appropriate method crucial optimal decision-making. All methods heavily affected by individual or group preferences therefore even a small change can cause rank-reversal. With regular proliferation such their modifications, it important carry out comparative study that provides comprehensive insight into performances under uncertain conditions. In this paper, we use Monte Carlo simulation approach empirically compare results five well-known widely applied methods, WSM, WPM, TOPSIS, GRA, MULTIMOORA different levels uncertainty. The findings paper will assist decision-makers most robust reliable for decision scenarios. research significant additions current repository knowledge multi-criteria analysis as well literature pertaining information systems. It also insights many managerial applications these methods.