Multiple Attribute Decision Making (MADM) refers to the problem of selecting among alternatives associated with multiple, usually conflicting, attributes. Based on incomplete preference information on alternatives given by the Decision Maker (DM), this paper proposes an mathematical programming approach to solve the MADM problem. To reflect the DM’s preference information, an optimization model...

As one of the emerging renewable resources, the use of photovoltaic cells has become a promise for offering clean and plentiful energy. The selection of a best photovoltaic cell for a promoter plays a significant role in aspect of maximizing income, minimizing costs and conferring high maturity and reliability, which is a typical multiple attribute decision making (MADM) problem. Although many ...

A new method for solving intuitionistic fuzzy multi-attribute decision making problem is proposed, in which the information of attribute weights is incompletely known. Considering much information about hesitancy and vagueness inherited to intuitionistic fuzzy sets, a new class of distance for describing the deviation degrees between intuitionistic fuzzy sets is introduced. Furthermore, the mea...

We present the Concordant-Ranks (CR) strategy that decision makers use to quickly find an alternative that is proximate to an ideal alternative in a multi-attribute decision space. CR implies that decision makers prefer alternatives that exhibit concordant ranks between attribute values and attribute weights. We show that, in situations where the alternatives are equal in multi-attribute utilit...

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 ...

When faced with a limited budget to collect data in support of a multiple attribute selection decision, the decisionmaker must decide how many samples to observe from each alternative and attribute. This allocation decision is of particular importance when the observation process is uncertain, such as with physical measurements. For example, when the U.S. Department of Homeland Security must de...

This paper introduces two virtual decision making units (DMUs) called ideal DMU (IDMU) and anti-ideal DMU (ADMU) into the data envelopment analysis (DEA). The resultant DEA models are, respectively, referred to as the data envelopment analysis with ideal and anti-ideal decision making units. One evaluates DMUs from the viewpoint of the best possible relative efficiency, while the other evaluate...

The paper investigates a technique for order preference by similarity to ideal solution (TOPSIS) method to solve multi-attribute decision making problems with bipolar neutrosophic information. We define Hamming distance function and Euclidean distance function to determine the distance between bipolar neutrosophic numbers. In the decision making situation, the rating of performance values of th...