Ranking alternatives (both qualitative as well as quantitative) in a multicriterion environment, employing experts opinion (preference structure) using fuzzy numbers and linguistic variables, are presented in this paper. Fuzzy weights (wJ i ) of alternatives (A i ) are computed using standard fuzzy arithmetic. Concept of maximizing set and minimizing set is introduced to decide total utility or...

This paper processes a unification of Fuzzy TOPSIS and Data Envelopment Analysis DEA to select the units with most efficiency. This research is a two-stage model designed to fully rank the organizational alternatives, where each alternative has multiple inputs and outputs. First, the alternative evaluation problem is formulated byData Envelopment Analysis DEA and separately formulates each pair...

-Group support systems (GSS) are increasingly being used within organizations to support group work. One area of support that is often desired is the scoring and ranking of alternatives on qualitative/subjective domains. In this article, we present a new, conceptual approach, the qualitative discriminant process, for scoring and ranking in GSS. This approach is based on well-established decisio...

Multi-criteria analysis (MCA) is being used in the Sediment and Society project as a tool for communicating impacts, as a tool for documenting differences in interests of stakeholder groups, and as a tool for ranking complex sediment remediation alternatives. Ranking of alternatives in MCA requires impacts to be (i) standardised, and then (ii) weighted against one another. This Technical Brief ...

Multiple attributes group decision making problems aim to find the best alternative for the experts from a solution set of alternatives. Because the attribute value and decision-makers evaluation with respect to the alternatives are usually vague and imprecise, fuzzy multiple attributes group decision making have been widely investigated, in which, ordering fuzzy evaluation results in fuzzy dec...

The prediction of structured outputs in general and rankings in particular has attracted considerable attention in machine learning in recent years, and different types of ranking problems have already been studied. In this paper, we propose a generalization or, say, relaxation of the standard setting, allowing a model to make predictions in the form of partial instead of total orders. We inter...

A well-studied approach to the design of voting rules views them as maximum likelihood estimators; given votes that are seen as noisy estimates of a true ranking of the alternatives, the rule must reconstruct the most likely true ranking. We argue that this is too stringent a requirement, and instead ask: How many votes does a voting rule need to reconstruct the true ranking? We define the fami...

the sensitivity analysis for multi-attribute decision making (madm) problems is important for two reasons: first, the decision matrix as the source of the results of a decision problem is inaccurate because it sorts the alternatives in each criterion inaccurately. second, the decision maker may change his opinions in a time period because of changes in the importance of the criteria and in the ...

In a two period decision problem, we study individuals who, in the second period, may be tempted by ex ante inferior choices. Individuals have preferences over sets of alternatives that represent the feasible choices in the second period. Our axioms yield a representation that identifies the individual’s commitment ranking, her temptation ranking, and her cost of selfcontrol. We provide an axio...

A well-studied approach to the design of voting rules views them as maximum likelihood estimators; given votes that are seen as noisy estimates of a true ranking of the alternatives, the rule must reconstruct the most likely true ranking. We argue that this is too stringent a requirement, and instead ask: How many votes does a voting rule need to reconstruct the true ranking? We define the fami...