Data mining is a powerful tool for firms to extract knowledge from their customers’ transaction data. One of the useful applications of data mining is segmentation. Segmentation is an effective tool for managers to make right marketing strategies for right customer segments. In this study we have segmented retailers of a hygienic manufacture. Nowadays all manufactures do understand that for st...

Interval type-2 fuzzy sets, each of which is characterized by the footprint of uncertainty, are a very useful means to depict the linguistic information in the process of decision making. In this article, we investigate the group decision making problems in which all the linguistic information provided by the decision makers is expressed as interval type-2 fuzzy decision matrices where each of ...

In group decision making with linguistic information, the decision makers (DMs) usually provide their assessment information by means of linguistic variables. In some situations, however, the DMs may provide fuzzy linguistic information because of time pressure, lack of knowledge, and their limited attention and information processing capabilities. In this paper, we introduce the concepts of tr...

Zinc is a high-level constraint modelling language with support for decision variables of complex types. Current constraint solvers only support decision variables of a subset of the types Zinc offers. Therefore, these variables and the constraints that involve them need to be reduced to a form that is supported by the target solvers. In this paper, we show how to reduce the type of decision va...

We ropose in this paper a new exact algorithm and gr aduay improvement methods of minimizing binary decision diagrams (BDD’s). In the exact minimization algorithm the o timum order is searched by the exchanges o! variabyes of BDD’s based on the framework of Friedman’s algorithm. The use of BDD representation of a given function and intermediate functions makes it possible to introduce pruning i...

Considering probability theory in which the semifield of positive real numbers is replaced by the idempotent semifield of real numbers (union infinity) endowed with the min and plus laws leads to a new formalism for optimization. Probability measures correspond to minimums of functions that we call cost measures, whereas random variables correspond to constraints on these optimization problems ...

This paper applies some general concepts in decision theory to a simple instrumental variables model. There are two endogenous variables linked by a single structural equation; k of the exogenous variables are excluded from this structural equation and provide the instrumental variables (IV). The reduced-form distribution of the endogenous variables conditional on the exogenous variables corres...

To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables (which follow a probability distribution). They combine together the best features of traditional constraint satisfaction, stochastic integer programming, and sto...

this paper offers an approach that could be useful for diverse types of layout problems or even area allocation problems. by this approach there is no need to large number of discrete variables and only by few continues variables large-scale layout problems could be solved in polynomial time. this is resulted from dividing area into discrete and continuous dimensions. also defining decision var...

Ala~traet--Errors-in-variables problems are considered for the case of three variables, where the underlying relations among the noise-free variables are linear, and covariance information for the noisy variables is available. The static problem where the variables are complex (which can arise when narrowband filtering is used) is analysed in detail. Some results are also presented for the case...