16 research outputs found

    Generalized intuitionistic fuzzy laplace transform and its application in electrical circuit

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    In this paper we describe the generalized intuitionistic fuzzy laplace transform method for solving first order generalized intutionistic fuzzy differential equation. The procedure is applied in imprecise electrical circuit theory problem. Here the initial condition of those applications is taken as Generalized Intuitionistic triangular fuzzy numbers (GITFNs).Publisher's Versio

    An Efficient Ranking Technique for Intuitionistic Fuzzy Numbers with Its Application in Chance Constrained Bilevel Programming

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    The aim of this paper is to develop a new ranking technique for intuitionistic fuzzy numbers using the method of defuzzification based on probability density function of the corresponding membership function, as well as the complement of nonmembership function. Using the proposed ranking technique a methodology for solving linear bilevel fuzzy stochastic programming problem involving normal intuitionistic fuzzy numbers is developed. In the solution process each objective is solved independently to set the individual goal value of the objectives of the decision makers and thereby constructing fuzzy membership goal of the objectives of each decision maker. Finally, a fuzzy goal programming approach is considered to achieve the highest membership degree to the extent possible of each of the membership goals of the decision makers in the decision making context. Illustrative numerical examples are provided to demonstrate the applicability of the proposed methodology and the achieved results are compared with existing techniques

    Development of Causal Model of Sustainable Hospital Supply Chain Management Using the Intuitionistic Fuzzy Cognitive Map (IFCM) Method

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    Purpose: Service industry is a massive sector accounting for about two-thirds of GDP of developed economies and is the field of an intensive competition between service companies and their supply chains. As a result, service supply chain management has become a subject of growing interest to researchers and business analysts. Healthcare industry is among the largest service industries with the highest potential for improvement in sustainability performance. The purpose of this study was to identify the concepts influencing the sustainability of hospital supply chain and provide a causal model for sustainable supply chain of hospital service. two aspects of contribution are identified for this research. Design/methodology/approach: In this study, concepts that influence the sustainability of a hospital service supply chain were identified by in-depth interviewing of 18 experts in hospitals of Kerman, Iran. Delphi method was used to reorganize the initial concepts into 15 concepts, Thus, a framework for sustainable supply chain of the hospital is proposed in the present study. This is the first contribution of this study. The second contribution is using the intuitive fuzzy cognitive map method for the relationship between extracted concepts. Findings: Delphi method was used to reorganize 68 initial concepts into 15 concepts Contains: demand management, resource and capacity management, customer relationship management, supplier relationship management, service management, information management, financial performance management, Attention to the environment, contamination, energy consumption, legal requirements, employees, community and stakeholders, social accountability and business ethics. The results indicate that service delivery management is highly central among other concepts. Originality/value: with focusing on concepts such as service management, and capacity and resources management, The sustainability of the hospital supply chain can be improved.Peer Reviewe

    B-spline curve interpolation model by using intuitionistic fuzzy approach

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    In this paper, B-spline curve interpolation model by using intuitionistic fuzzy set approach is introduced. Firstly, intuitionistic fuzzy control point relation is defined based on the intuitionistic fuzzy concept. Later, the intuitionistic fuzzy control point relation is blended with B-spline basis function. Through interpolation method, intuitionistic fuzzy B-spline curve model is visualized. Finally, some numerical examples and an algorithm to generate the desired curve is shown

    B-spline curve interpolation model by using intuitionistic fuzzy approach

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    In this paper, B-spline curve interpolation model by using intuitionistic fuzzy set approach is introduced. Firstly, intuitionistic fuzzy control point relation is defined based on the intuitionistic fuzzy concept. Later, the intuitionistic fuzzy control point relation is blended with B-spline basis function. Through interpolation method, intuitionistic fuzzy B-spline curve model is visualized. Finally, some numerical examples and an algorithm to generate the desired curve is shown

    3-tuple Bézier surface interpolation model for data visualization

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    In this paper, the 3-tuple Bézier surface interpolation model is introduced. The 3-tuple control net relation is defined through intuitionistic fuzzy concept. Later, the control net is blended with Bernstein basis function to obtain surface blending function and to produce 3-tuple Bézier surface. The 3-tuple Bézier surface model is illustrated through the interpolation method by using data point with intuitionistic features. Some numerical example is shown. Lastly, the 3-tuple Bézier surface properties is also discussed

    Simplified Neutrosophic Sets Based on Interval Dependent Degree for Multi-Criteria Group Decision-Making Problems

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    In this paper, a new approach and framework based on the interval dependent degree for multi-criteria group decision-making (MCGDM) problems with simplified neutrosophic sets (SNSs) is proposed. Firstly, the simplified dependent function and distribution function are defined. Then, they are integrated into the interval dependent function which contains interval computing and distribution information of the intervals

    Approaches to multi-attribute group decision-making based on picture fuzzy prioritized Aczel–Alsina aggregation information

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    The Aczel-Alsina t-norm and t-conorm were derived by Aczel and Alsina in 1982. They are modified forms of the algebraic t-norm and t-conorm. Furthermore, the theory of picture fuzzy values is a very valuable and appropriate technique for describing awkward and unreliable information in a real-life scenario. In this research, we analyze the theory of averaging and geometric aggregation operators (AOs) in the presence of the Aczel-Alsina operational laws and prioritization degree based on picture fuzzy (PF) information, such as the prioritized PF Aczel-Alsina average operator and prioritized PF Aczel-Alsina geometric operator. Moreover, we examine properties such as idempotency, monotonicity and boundedness for the derived operators and also evaluated some important results. Furthermore, we use the derived operators to create a system for controlling the multi-attribute decision-making problem using PF information. To show the approach's effectiveness and the developed operators' validity, a numerical example is given. Also, a comparative analysis is presented
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