Rank reversal in decision making is a common phenomenon resulting in confusion and ambiguity in selection procedure especially while multiple multi-criteria decision making (MCDM) techniques are independently applied. To eradicate this confusion, this paper proposes a novel MCDM methodology namely Technique of Accurate Ranking Order (TARO). The TARO method is an extension of conventional MCDM approaches. The proposed method commences at the end of conventional methodologies with the final selection values. The proposed technique, using an advanced version of entropy weighting method, initially measures weights of the final selection values. Subsequently, based on the final section values and their computed weights, TARO measures accurate selection indices that determine the accurate ranking order of the alternatives. The proposed technique is illustrated by three real life examples on robot selection problems. The results obtained by TARO justify the validity, applicability and requirements of the proposed techniques for proper decision making under the MCDM environment.

In this paper, the ranking performance of six most popular and easily comprehensive multi-criteria decision-making (MCDM) methods, i.e. weighted sum method (WSM), weighted product method (WPM), weighted aggregated sum product assessment (WASPAS) method, multi-objective optimization on the basis of ratio analysis and reference point approach (MOORA) method, and multiplicative form of MOORA method (MULTIMOORA) is investigated using two real time industrial robot selection problems. Both single dimensional and high dimensional weight sensitivity analyses are performed to study the effects of weight variations of the most important as well as the most critical criterion on the ranking stability of all the six considered MCDM methods. The identified local weight stability interval indicates the range of weights within which the rank of the best alternative remains unaltered, whereas, the global weight stability interval determines the range of weights within which the overall rank order of all the alternatives remains unaffected. It is observed that for both the problems, multiplicative form of MOORA is the most robust method being least affected by the changing weights of the most important and the most critical criteria.