DECISION MAKING UNDER LINGUISTIC UNCERTAINTY CONDITIONS ON BASE OF GENERALIZED FUZZY NUMBERS

This article is devoted to the problem of decision making under linguistic uncertainty. The effective method for modelling linguistic uncertainty is the fuzzy set theory. There are several types of fuzzy number types proposed by L. Zadeh: fuzzy type-1, fuzzy type-2, Z-numbers. Chen proposed concept of generalized fuzzy numbers. Generalized trapezoidal fuzzy numbers (GTFN) one of effective approach which can be used for modeling linguistic uncertainty. GFTN very convenient model which allow take in account second order uncertainty. GFTN are formalized and major operations are described as practical problem is considered group decision making for supplier selection. In this case the criteria assessments are expressed by experts in linguistic form. Group decision making model is presented as 2 step aggregation procedure, in first step is aggregated value of alternative by expert, in second step by criteria. Numerical example with four criteria and three alternatives are presented and solved.

A dynamic generalized fuzzy multi-criteria croup decision making approach for green supplier segmentation

Supplier selection and segmentation are crucial tasks of companies in order to reduce costs and increase the competitiveness of their goods. To handle uncertainty and dynamicity in the supplier segmentation problem, this research thus proposes a new dynamic generalized fuzzy multi-criteria group decision making (MCGDM) approach from the aspects of capability and willingness and with respect to environmental issues. The proposed approach defines the aggregated ratings of alternatives, the aggregated weights of criteria, and the weighted ratings by using generalized fuzzy numbers with the effect of time weight. Next, we determine the ranking order of alternatives via a popular centroid-index ranking approach. Finally, two case studies demonstrate the efficiency of the proposed dynamic approach. The applications show that the proposed appoach is effective in solving the MCGDM in vague environment.

RAM assessment of the repairable industrial structure with genuine human-mistake working conditions with generalized fuzzy numbers

PurposeThe present paper investigated a skim milk powder production plant with genuine human mistake for analyzing its performance in terms of its reliability, availability and maintainability (RAM) indices along with mean time between failure (MTBF) and expected number of failure (ENOF).Design/methodology/approachIn the proposed work, the generalized fuzzy lambda–tau methodology has been used to carry out the analysis of the repairable structure using the improved arithmetic operations for generalized fuzzy numbers by considering the degree of confidence levels.FindingsRAM indices along with MTBF and ENOF are obtained to increase the quality of skim milk powder manufacturing structures of a dairy plant with genuine human-mistake working conditions.Originality/valueIn the present paper, a mathematical model for a complex industrial system based on fuzzy has been developed. Finally, the results are more realistic and comprehensive for the decision-maker for farther application.

МОДЕЛИРОВАНИЕ ЛИНГВИСТИЧЕСКОЙ НЕОПРЕДЕЛЕННОСТИ НА ОСНОВЕ Z-ЧИСЕЛ В СИСТЕМАХ МНОГОКРИТЕРИАЛЬНОГО ПРИНЯТИЯ РЕШЕНИЙ

The article is devoted to the problem of multi criteria decision making under linguistic uncertainty. Information of different approaches for modelling linguistic uncertainty have been analyzed. The concept of z- numbers proposed by L. Zadeh have been presented. Z-number is presented as cortege of two fuzzy number A and B, where A is analyzed factor, B is reliability of an assessment. The method of conversion z- numbers into generalized fuzzy numbers have been applied. As test problem have been used supplier selection problem. As decision making model have been used group weighted average method. All calculations and results were presented.