supplier selection is one of the most important activities of purchasing departments. this importance is increased even more by new strategies in a supply chain, because of the key role suppliers perform in terms of quality, costs and services which affect the outcome in the buyer’s company. supplier selection is a multiple criteria decision making problem in which the objectives are not equall...

The well-known generalisation of hard Cmeans (HCM) clustering is fuzzy C-means (FCM) clustering where a weight exponent on each fuzzy membership is introduced as the degree of fuzziness. An alternative generalisation of HCM clustering is proposed in this paper. This is called fuzzy entropy (FE) clustering where a weight factor of the fuzzy entropy function is introduced as the degree of fuzzy e...

Crisp comparison matrices produce crisp weight estimates. It is logical for an interval or fuzzy comparison matrix to give an interval or fuzzy weight estimate. In this paper, an eigenvector method (EM) is proposed to generate interval or fuzzy weight estimate from an interval or fuzzy comparison matrix, which differs from Csutora and Buckley’s LambdaMax method in several aspects. First, the pr...

The design of weight is one of the important parts in fuzzy decision making, as it would have a deep effect on the evaluation results. Entropy is one of the weight measure based on objective evaluation. Non--probabilistic-type entropy measures for fuzzy set and interval type-2 fuzzy sets (IT2FS) have been developed and applied to weight measure. Since the entropy for (IT2FS) for decision making...

this paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. the classification performance andinterpretability are of major importance in these systems. in this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). ourapproach uses a punish...

In fuzzy rule-based classification systems, rule weight has often been used to improve the classification accuracy. In past research, a number of heuristic methods for rule weight specification have been proposed. In this paper, a method of fuzzy rule weight specification using Receiver Operating Characteristic (ROC) analysis is proposed. In order to specify the weight of a fuzzy rule, using 2-...

A new method for feature extraction and recognition, namely the fuzzy bidirectional weighted sum criterion (FBWSC) is proposed in this paper. FBWSC defines the row directional fuzzy image optimal image projection matrix. Subsequently, each sample in the original training sample set is transformed using the row directional optimal image projection matrix, and the row directional feature training...

In this paper, we incorporate the concept of fuzzy set theory into the support vector regression (SVR). In our proposed method, target outputs of training samples are considered to be fuzzy numbers and then, membership function of actual output (objective hyperplane in high dimensional feature space) is obtained. Two main properties of our proposed method are: (1) membership function of actual ...