In this paper, we present a new method for fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads. First, we present a new method for ranking generalized fuzzy numbers. The proposed method considers the defuzzified values, the heights and the spreads for ranking generalized fuzzy numbers. Based on the proposed method for ranking generalized f...

Fuzzy Hamming Distance is successfully used in a Content-Based Image Retrieval (CBIR) system as a similarity measure. The system performs a m × n partitioning of the compared images and for each partitions pairs evaluates FHD. In the last step the FHD are defuzzified and the results are combined in a final score. In order to take full advantage of the use of fuzzy sets, the current study invest...

Type-2 defuzzification is a two-stage process. Type-reduction, the first stage, gives rise to a type-1 fuzzy set known as the type-reduced set (TRS), which for the second stage is defuzzified to give a crisp number. This paper focusses on the TRS itself, which reveals a fascinating internal structure. We provide a description of and explanation for this structure, then go on to suggest how it m...

This paper will present a novel method based on harmonic mean, geometric mean, arithmetic mean and root mean square to help reduce fuzzy rules. The objective of the new method proposed is to produce fuzzy models with both a small number of interpretable rules and sufficiently high precision. Comparisons will be made between systems utilizing reduced rules and original rules to verify efficacy o...

Defuzzification of type-2 fuzzy sets is a computationally intense problem. This paper proposes a new approach for defuzzification of interval type-2 fuzzy sets. The collapsing method converts an interval type-2 fuzzy set into a representative embedded set (RES) which, being a type-1 set, can then be defuzzified straightforwardly. The novel Representative Embedded Set Theorem (REST), with which ...

The purpose of this paper is to study fully fuzzy multi-choice multiobjective linear programming problem (FFMMOLPP), in which, right hand side of each constraint has two choices. With the help of ranking function, deviation distance and deviation degree between two fuzzy numbers are defined. A new method is proposed to find the  fuzzy pareto optimal solution of FFMMOLPP which is defuzzified by...

This model presents the invention scheduling difficulty in industry with different operational constraints, as well as strategic plan of the business, revenue purpose, and limit on finishing. In this article, we have studied an inventory model for deteriorating items with shortages under partially backlogging. The aim of present study is to minimize the total cost function in fuzzy environment....

The main features of the fuzzy sets and their corresponding membership functions were presented in terms fuzzification process further by de-fuzzification operation. convexity α -(alfa) cuts is used decomposition sets. alfa defined precisely pair lowest upper greatest lower bounds. convex combination intervals sub-regions function considered as points defuzzified values methods to crisp formula...

We propose a reformulation of the problem of making a decision with multiple objectives in terms of fuzzy scores and their consistent defuzzification, with respect to the logical point of view taken into account. The objectives are seen as subsets (or events) of a universal set U and the degree to which an alternative Ai satisfies the objective Oj is a conditional fuzzy event Ai|Oj , represente...

The paper aims at designing new strategies to extend the selection step of traditional Differential Evolution for Multi-objective Optimization algorithm to proficiently obtain Pareto-optimal solutions in presence of noise. The first strategy, referred to as adaptive selection of sample size, is employed to balance the trade-off between accurate fitness estimate and computational complexity. The...