Himpunan Kabur Hesitant Ganda yang Diperluas (Expanded Dual Hesitant Fuzzy Sets)

Konsep Expanded Dual Hesitant Fuzzy Sets merupakan suatu pengembangan dari konsep Hesitant Fuzzy Sets. Berdasarkan konsep Hesitant Fuzzy Sets telah diperoleh beberapa konsep seperti Dual Hesitant Fuzzy Sets, Expanded Hesitant Fuzzy Sets, dan Extended Hesitant Fuzzy Sets yang menjadi konsep dasar pengembangan Expanded Dual Hesitant Fuzzy Sets. Kemudian akan dikaji beberapa operasi-operasi terkait Expanded Dual Hesitant Fuzzy Sets, skor pada Expanded Dual Hesitant Fuzzy Sets, hukum perbandingan, dan penerapan konsep Expanded Dual Hesitant Fuzzy Sets dalam masalah pengambilan keputusan

Extended hesitant fuzzy sets

Hesitant fuzzy sets (HFSs) are a useful tool to manage situations in which the decision makers (DMs) hesitate about several possible values for the membership to assess a variable, alternative, etc. However, HFSs have the information loss problem and cannot identify different DMs, which interferes with the application of HFSs in decision making. To overcome these limitations, we develop the extended hesitant fuzzy sets (EHFSs) in this paper. As an extension of HFSs, EHFSs have close relationships with existing fuzzy sets including intuitionistic fuzzy sets (IFSs), fuzzy multisets (FMSs), type-2 fuzzy sets (T2FSs), dual hesitant fuzzy sets (DHFSs), and especially HFSs. We propose a concept of extended hesitant fuzzy elements (EHFEs), then study the basic operations and the desirable properties of EHFEs in detail. Some extended hesitant distance measures are developed to illustrate their advantages comparing with the existing hesitant distance measures. To extend EHFSs to decision making, we combine the proposed distance measures with the Dempster-Shafer belief structure. First published online: 15 Jun 201

Intertemporal Choice of Fuzzy Soft Sets

This paper first merges two noteworthy aspects of choice. On the one hand, soft sets and fuzzy soft sets are popular models that have been largely applied to decision making problems, such as real estate valuation, medical diagnosis (glaucoma, prostate cancer, etc.), data mining, or international trade. They provide crisp or fuzzy parameterized descriptions of the universe of alternatives. On the other hand, in many decisions, costs and benefits occur at different points in time. This brings about intertemporal choices, which may involve an indefinitely large number of periods. However, the literature does not provide a model, let alone a solution, to the intertemporal problem when the alternatives are described by (fuzzy) parameterizations. In this paper, we propose a novel soft set inspired model that applies to the intertemporal framework, hence it fills an important gap in the development of fuzzy soft set theory. An algorithm allows the selection of the optimal option in intertemporal choice problems with an infinite time horizon. We illustrate its application with a numerical example involving alternative portfolios of projects that a public administration may undertake. This allows us to establish a pioneering intertemporal model of choice in the framework of extended fuzzy set theorie

The Selection of Investment Priorities using Expanded Dual Hesitant Fuzzy Sets

The concept of expanded dual hesitant fuzzy set is a concept that can be applied in decision-making problems. In decision-making problems, expanded dual hesitant fuzzy set can be applied to represent the opinions of multiple experts or stakeholders in a more elaborate manner. It enables decision-makers to provide more detailed information about their preferences and hesitancy

Decision making with both diversity supporting and opposing membership information

Online big data provides large amounts of decision information to decision makers, but supporting and opposing information are present simultaneously. Dual hesitant fuzzy sets (DHFSs) are useful models for exactly expressing the membership degree of both supporting and opposing information in decision making. However, the application of DHFSs requires an improved distance measure. This paper aims to improve distance measure models for DHFSs and apply the new distance models to generate a technique for order preference by similarity to an ideal solution (TOPSIS) method for multiple attribute decision making (MADM)

Dual Hesitant N-Soft Sets

In this article, we introduce a new hybrid model called Dual Hesitant N-Soft Sets (DHNSS). This new model is clarified and reformulated as a combination of dual and hesitancy with N-soft sets. We investigate the basic operations of DHNSS. Our novel model is illustrated with real life examples. Moreover, we propose the decision making algorithm to see the application of this model

Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions

This paper introduces and investigates ranked hesitant fuzzy sets, a novel extension of hesitant fuzzy sets that is less demanding than both probabilistic and proportional hesitant fuzzy sets. This new extension incorporates hierarchical knowledge about the various evaluations submitted for each alternative. These evaluations are ranked (for example by their plausibility, acceptability, or credibility), but their position does not necessarily derive from supplementary numerical information (as in probabilistic and proportional hesitant fuzzy sets). In particular, strictly ranked hesitant fuzzy sets arise when no ties exist, i.e., when for any fixed alternative, each submitted evaluation is either strictly more plausible or strictly less plausible than any other submitted evaluation. A detailed comparison with similar models from the literature is performed. Then in order to produce a natural strategy for multi-criteria multi-agent decisions with ranked hesitant fuzzy sets, canonical representations, scores and aggregation operators are designed in the framework of ranked hesitant fuzzy sets. In order to help implementation of this model, Mathematica code is provided for the computation of both scores and aggregators. The decision-making technique that is prescribed is tested with a comparative analysis with four methodologies based on probabilistic hesitant fuzzy information. A conclusion of this numerical exercise is that this methodology is reliable, applicable and robust. All these evidences show that ranked hesitant fuzzy sets are an intuitive extension of the hesitant fuzzy set model designed by V. Torra, that can be implemented in practice with the aid of computationally assisted algorithms.Junta de Castilla y León y European Regional Development Fun

DUAL – HESITANT FUZZY TRANSPORTATION PROBLEM

So on handle inexact, tentative or partial information and knowledge circumstances in factual-life operational investigate predicaments dual-hesitant fuzzy set is applied. during this work a totally unique method called Allocation Table Method (ATM) for solving dual-hesitant fuzzy transportation problem is introduced. This method is explained with a numerical example and thus the result obtained through this method is compared with the prevailing method (VAM). This proposed method gives an optimum solution as compared with other metho