Fuzzy sets and their variants
Zanyar A. Ameen
Abstract
Thangaraj and Balasubramanian introduced the so-called somewhat fuzzy semicontinuous and somewhat fuzzy semiopen functions. Two years later, the same authors defined two other types of functions called somewhat fuzzy continuous and somewhat fuzzy open without indicating connections between them. At first ...
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Thangaraj and Balasubramanian introduced the so-called somewhat fuzzy semicontinuous and somewhat fuzzy semiopen functions. Two years later, the same authors defined two other types of functions called somewhat fuzzy continuous and somewhat fuzzy open without indicating connections between them. At first glance, we may easily conclude (from their definitions) that every somewhat fuzzy continuous (resp. open) function is somewhat fuzzy semicontinuous (resp. semiopen) but not conversely. In this note, we show that they are equivalent. We further prove that somewhat fuzzy continuous functions are weaker than fuzzy semicontinuous functions.- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - -- - - - - - - - - - - - - - - - - - - - - - - - -
Fuzzy sets and their variants
SUNDAY ADESINA ADEBISI; Florentin Smarandache
Abstract
Abstract The neutrosophic interval statistical number (NISN) has been known to be very useful in expressing the interval values under indeterminate environments. One of the essential and so important useful as tools for measuring the degree of similarity between sets of given objects is the similarity ...
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Abstract The neutrosophic interval statistical number (NISN) has been known to be very useful in expressing the interval values under indeterminate environments. One of the essential and so important useful as tools for measuring the degree of similarity between sets of given objects is the similarity measure . In this paper, neutrosophic numbers as well as the generalized Dice similarity measure for neutrosophic numbers for two sets are defined after which the axioms of fuzziness similarity and symmetry satisfying the NISN the properties were proved.
Fuzzy sets and their variants
Khushdil Ahmad; Muhammad Waseem Asghar
Abstract
In this paper, we define the term of η-fuzzy subgroup and show that every fuzzy subgroup is a η-fuzzy subgroup. We define some of the algebraic properties of the concept of η-fuzzy cosets. Furthermore, we initiate the study of η-fuzzy normal subgroup and quotient group with respect to the η-fuzzy ...
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In this paper, we define the term of η-fuzzy subgroup and show that every fuzzy subgroup is a η-fuzzy subgroup. We define some of the algebraic properties of the concept of η-fuzzy cosets. Furthermore, we initiate the study of η-fuzzy normal subgroup and quotient group with respect to the η-fuzzy normal subgroup and demonstrate some of their various group theoretical properties.
Fuzzy sets and their variants
Sunday Adesina Adebisi; Mike Ogiugo; Michael Enioluwafe
Abstract
Abstract The term fuzzy logic is generic as it can be used to describe the likes of fuzzy arithmetic, fuzzy mathematical programming, fuzzy topology, fuzzy graph theory ad fuzzy data analysis which are customarily called fuzzy set theory. The aspect of pure Mathematics has undergone a lot of dynamic ...
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Abstract The term fuzzy logic is generic as it can be used to describe the likes of fuzzy arithmetic, fuzzy mathematical programming, fuzzy topology, fuzzy graph theory ad fuzzy data analysis which are customarily called fuzzy set theory. The aspect of pure Mathematics has undergone a lot of dynamic developments over the years. Since inception , the study has been extended to some other important classes of finite abelian and nonabelian groups such as the dihedral , quaternion, semidihedral, and hamiltonian groups. Other different approaches have been so far, applied for the classification. Every finite p-group is nilpotent. The nilpotence property is an hereditary one. Thus, every finite p-group possesses certain remarkable characteristics. Efforts are carefully being intensified to calculate , in this paper, the explicit formulae for the number of distinct fuzzy subgroups of the Cartesian product of the dihedral group of order 25 with a cyclic group of order of an n power of two for, which n ≥ 5.
Fuzzy sets and their variants
Besma Belhadj
Abstract
Under the additional assumption that the errors are normally distributed, the Ordinary Least Squares (OLS) method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the OLS method based on a so-called Gaussian membership function, ...
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Under the additional assumption that the errors are normally distributed, the Ordinary Least Squares (OLS) method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the OLS method based on a so-called Gaussian membership function, one that checks the validity of the verbal explanation suggested by the observer. The fuzzy estimation approach demonstrated here is based on a suitable framework for a natural behavior observed in nature. An application based on a group of MENA countries in 2015 is presented to estimate the employment poverty relationship.Under the additional assumption that the errors are normally distributed, the ordinary least squares method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the ordinary least squares method based on a so-called Gaussian membership function, one that checks the validity of the verbal explanation suggested by the observer. The fuzzy estimation approach demonstrated here is based on a suitable framework for a natural behavior observed in nature. An application based on a group of MENA countries in 2015 is presented to estimate the Employment Poverty relationship.
Fuzzy sets and their variants
Nivetha Martin; A.Velankanni Ananth; P.K. Sharmila; T. Priya
Abstract
The pandemic has created a wide range of impacts on the livelihood of the people especially in their occupation and income generation. The horrific pandemic impacts have caused the populace to switch their occupations for the sake of their livelihood sustainability. This research works aims in determining ...
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The pandemic has created a wide range of impacts on the livelihood of the people especially in their occupation and income generation. The horrific pandemic impacts have caused the populace to switch their occupations for the sake of their livelihood sustainability. This research works aims in determining the impacts of the occupational shifts especially in case of rural populace. The decision-making method of Fuzzy Cognitive Maps (FCM) is used in combinations with the statistical data collection methods of survey methodology, participatory approach and multi stage purposive sampling. It is observed that a significant percentage of people have shifted from their occupation and the occupational shifts have impacts on the personal, economic, social and health dimensions of the rural populace. The factors under each dimension and their inter associational impacts are also determined using the method of FCM and FCM Expert software. Based on the findings of the research work, it is very evident that the occupational shifts have created a lot of impacts on the livelihood of the rural populace and also each of the person has experienced the impacts more personally. The societal contribution of the research lies in communicating the results and inferences to the concerned administrators so as to facilitate the affected rural populace in getting back to their primary occupation.
Fuzzy sets and their variants
Leonce Leandry; Innocent Sosoma; David Koloseni
Abstract
Currently fuzzy set theory has a wide range to model real life problems with incomplete or vague information which perfectly suits the reality and its application is theatrically increasing. This work explored the basic fuzzy operations with the Gaussian Membership using the α-cut method. As it ...
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Currently fuzzy set theory has a wide range to model real life problems with incomplete or vague information which perfectly suits the reality and its application is theatrically increasing. This work explored the basic fuzzy operations with the Gaussian Membership using the α-cut method. As it is known that, the Gaussian membership function has a great role in modelling the fuzzy problems this is what impelled to explore its operation which can further be used in analysis of fuzzy problems. Primarily the basic operations which has been discussed here are addition, subtraction, multiplication, division, reciprocal, exponential, logarithmic and nth power.
Fuzzy sets and their variants
Ceren Cubukcu; Cem Cantekin
Abstract
Covid-19 pandemic forced all the world to make significant changes in their daily routines. As a result, internet and digital technologies started to be used more actively by individuals and businesses. Due to this digitalization, everyone is more open to digital threats. In order to provide the security ...
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Covid-19 pandemic forced all the world to make significant changes in their daily routines. As a result, internet and digital technologies started to be used more actively by individuals and businesses. Due to this digitalization, everyone is more open to digital threats. In order to provide the security of the network, firewalls should be used. Firewalls act as a barrier between the internal and the external networks. Thus, it is more important than ever to choose the right firewall for each network. In this study, an integrated Fuzzy-Analytic Hierarchy Process (AHP) and TOPSIS model is introduced to find out the most suitable firewall. A survey is designed and used to generate the data of this study. This study distinguishes from other studies by proposing a solution which ranks the firewall alternatives using a combination of fuzzy-AHP and TOPSIS models. As a result, among the five different firewall alternatives, the second one is found out to be the best. A solution proposal ranking the firewall alternatives is new in the literature. This approach is used in many different Multi-Criteria Decision Making (MCDM) problems before but not in firewall selection. Hence, this study can be considered quite innovative in terms of the problem it handles and the model used. It offers a new solution related to a decision making problem that has started to gain more importance with the current digitalization process due to Covid-19 pandemic.
Fuzzy sets and their variants
Alireza Aliahmadi; Hamed Nozari; Javid Ghahremani-Nahr; Agnieszka Szmelter-Jarosz
Abstract
In recent years, the high complexity of the business environment, dynamism and environmental change, uncertainty and concepts such as globalization and increasing competition of organizations in the national and international arena have caused many changes in the equations governing the supply chain. ...
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In recent years, the high complexity of the business environment, dynamism and environmental change, uncertainty and concepts such as globalization and increasing competition of organizations in the national and international arena have caused many changes in the equations governing the supply chain. In this case, supply chain organizations must always be prepared for a variety of challenges and dynamic environmental changes. One of the effective solutions to face these challenges is to create a resilient supply chain. Resilient supply chain is able to overcome uncertainties and disruptions in the business environment. The competitive advantage of this supply chain does not depend only on low costs, high quality, reduced latency and high level of service. Rather, it has the ability of the chain to avoid catastrophes and overcome critical situations, and this is the resilience of the supply chain. AI and IoT technologies and their combination, called AIoT, have played a key role in improving supply chain performance in recent years and can therefore increase supply chain resilience. For this reason, in this study, an attempt was made to better understand the impact of these technologies on equity by examining the dimensions and components of the Artificial Intelligence of Things (AIoT)-based supply chain. Finally, using nonlinear fuzzy decision making method, the most important components of the impact on the resilient smart supply chain are determined. Understanding this assessment can help empower the smart supply chain.
Fuzzy sets and their variants
Sunday Adesina Adebisi; Mike Ogiugo; Michael Enioluwafe
Abstract
A group is nilpotent if it has a normal series of a finite length n. By this notion, every finite p-group is nilpotent. The nilpotence property is an hereditary one. Thus, every finite p-group possesses certain remarkable characteristics. In this paper, the explicit formulae is given for the number of ...
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A group is nilpotent if it has a normal series of a finite length n. By this notion, every finite p-group is nilpotent. The nilpotence property is an hereditary one. Thus, every finite p-group possesses certain remarkable characteristics. In this paper, the explicit formulae is given for the number of distinct fuzzy subgroups of the Cartesian product of the dihedral group of order 23 with a cyclic group of order of an m power of two for, which m ≥ 3.
Fuzzy sets and their variants
Taraneh Javanbakht; Shivanjan Chakravorty
Abstract
The present paper proposes a new application of the prediction of human behavior using TOPSIS as an appropriate tool for data optimization. Our hypothesis was that the analysis of the candidates with this method was influenced by the change of their behavior. We found that the behavior change could occur ...
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The present paper proposes a new application of the prediction of human behavior using TOPSIS as an appropriate tool for data optimization. Our hypothesis was that the analysis of the candidates with this method was influenced by the change of their behavior. We found that the behavior change could occur in more than one time span when the behavior of two candidates changed simultaneously. One of the advantages of this study is that the pattern of the behavior change with time is predicted with this method. Another advantage is that the modifications in the TOPSIS algorithm have made the predictions independent from the need of changing the fuzzy membership degrees of the candidates. This is the first time that these modifications in this technique with a new application including the numerical analysis of cognitive date are reported. Our results can be used in cognitive science, experimental psychology, cognitive informatics and artificial intelligence.
Fuzzy sets and their variants
Ibrahim Mohamed Mekawy
Abstract
This paper deals with a multi-objective linear fractional programming problem in fuzzy environment. The problem is considered by introducing all the parameters as piecewise quadratic fuzzy numbers. Through the use of the associated real number of the close interval approximation and the order relation ...
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This paper deals with a multi-objective linear fractional programming problem in fuzzy environment. The problem is considered by introducing all the parameters as piecewise quadratic fuzzy numbers. Through the use of the associated real number of the close interval approximation and the order relation of the piecewise quadratic fuzzy numbers, the problem is transformed into the corresponding crisp problem. A proposed method introduces to generate ideals and the set of all fuzzy efficient solutions. The advantage of it helps the decision maker to handle the real life problem. A numerical example is given illustrate the method.
Fuzzy sets and their variants
Irem Ucal Sari; Umut Ak
Abstract
Industry 4.0 implementations are competitive tools of recent production systems in which complex computerized systems are employed. Efficiency of these systems is generally measured by Data Envelopment Analysis (DEA) under certainty. However, the required data in modelling the system involve high degree ...
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Industry 4.0 implementations are competitive tools of recent production systems in which complex computerized systems are employed. Efficiency of these systems is generally measured by Data Envelopment Analysis (DEA) under certainty. However, the required data in modelling the system involve high degree of uncertainty, which necessitates the usage of fuzzy set theory. Fuzzy DEA models can successfully handle this problem and present efficient solutions for Industry 4.0 implementation. In this paper, efficiency of Industry 4.0 applications is measured by classical DEA and fuzzy DEA models, allowing the variables to have different units of measurement and to be independent from analytical production functions. Besides that, fuzzy algorithms for output-oriented DEA are proposed for BBC and CCR models. To the best of our knowledge, this article is the first quantitative academic study to measure the effects of Industry 4.0 applications on productivity. It also shows how fuzzy factors can affect decision-making by comparing fuzzy and classical DEA results. A real application of the models is realized in a company of home appliances manufacturing sector having Industry 4.0 applications. The effect of Industry 4.0 implementation on machine productivity, and superiority of fuzzy DEA over classical DEA are shown through the application.
Fuzzy sets and their variants
Satya Kumar Das
Abstract
In this article, we have developed a deteriorated multi-item inventory model in a fuzzy environment. Here the demand rate is constant. Production cost and set-up cost are the most vital issue in the inventory system of the market world. Here production cost and set-up- cost are continuous functions of ...
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In this article, we have developed a deteriorated multi-item inventory model in a fuzzy environment. Here the demand rate is constant. Production cost and set-up cost are the most vital issue in the inventory system of the market world. Here production cost and set-up- cost are continuous functions of demand. Set-up-cost is also dependent on average inventory level. Deterioration cost is the most challenging issue in the business world. So here deterioration cost is dependent on inventory level and demand. Lead time crashing cost is considered the continuous function of leading time. In the real world all cost are not fixed. Due to uncertainty all cost parameters of the proposed model are taken as Generalized Triangular Fuzzy Number (GTFN). The formulated multi objective inventory problem has been solved by various techniques like as Geometric Programming (GP) technique, Fuzzy Programming Technique with Hyperbolic Membership Function (FPTHMF), Fuzzy Non-Linear Programming (FNLP) technique. Numerical example is taken to illustrate the model. Sensitivity analysis and graphical representation have been shown to test the parameters of the model.
Fuzzy sets and their variants
Umutgül Bulut; Eren Ozceylan
Abstract
It has become one of the indispensable conditions to continuously improve the quality and achieve the quality standards in order to adapt to the increasingly competitive environment in the textile industry. However, the textile production process like many other industrial processes involves the interaction ...
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It has become one of the indispensable conditions to continuously improve the quality and achieve the quality standards in order to adapt to the increasingly competitive environment in the textile industry. However, the textile production process like many other industrial processes involves the interaction of a large number of variables. For a standard quality production, the relation between raw material properties, process parameters, and environmental factors must be established conclusively. The physical properties of air textured warp yarn that affect the quality of the yarn, construct the strength of the yarn. After the production process, different values of each yarn sample are revealed from the strength tests performed during the quality control process. Six criteria that affect the quality of the yarn and identify the strength of the yarn are defined as a result of strength tests. Those criteria are count, tenacity, elongation shrinkage, Resistance per Kilometer (RKM) and breaking force. The differences between the values of these criteria and linguistic variables cause uncertainty when defining the quality of the yarn. To take into consideration this uncertainty a Fuzzy Inference System (FIS) is developed using six criteria as inputs, 144 rules created, and the linguistic variables of Air Textured Yarn (ATY) samples of a textile manufacturer. The quality level of the products according to the different membership functions are identified with the proposed FIS generated by MATLAB version 2015a and recommendations are made to the manufacturer.
Fuzzy sets and their variants
Gia Sirbiladze
Abstract
The Ordered Weighted Averaging (OWA) operator was introduced by Yager [34] to provide a method for aggregating inputs that lie between the max and min operators. In this article we continue to present some extensions of OWA-type aggregation operators. Several variants of the generalizations of the ...
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The Ordered Weighted Averaging (OWA) operator was introduced by Yager [34] to provide a method for aggregating inputs that lie between the max and min operators. In this article we continue to present some extensions of OWA-type aggregation operators. Several variants of the generalizations of the fuzzy-probabilistic OWA operator-FPOWA (introduced by Merigo [13], [14]) are presented in the environment of fuzzy uncertainty, where different monotone measures (fuzzy measure) are used as uncertainty measures. The considered monotone measures are: possibility measure, Sugeno additive measure, monotone measure associated with Belief Structure and Choquet capacity of order two. New aggregation operators are introduced: AsFPOWA and SA-AsFPOWA. Some properties of new aggregation operators and their information measures are proved. Concrete faces of new operators are presented with respect to different monotone measures and mean operators. Concrete operators are induced by the Monotone Expectation (Choquet integral) or Fuzzy Expected Value (Sugeno Integral) and the Associated Probability Class (APC) of a monotone measure. New aggregation operators belong to the Information Structure I6 (see Part I, Section 3). For the illustration of new constructions of AsFPOWA and SA-AsFPOWA operators an example of a fuzzy decision-making problem regarding the political management with possibility uncertainty is considered. Several aggregation operators (“classic” and new operators) are used for the comparing of the results of decision making.
Fuzzy sets and their variants
Shaveta Arora; Renu Vadhera; Bharti Chugh
Abstract
COVID-19, an epidemic disease, has challenged human lives all over the world. Governments and scientific communities are trying their level best to help the masses. This disease which is caused by corona virus majorly attacks the upper respiratory system rendering the human immunity incapacitated and, ...
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COVID-19, an epidemic disease, has challenged human lives all over the world. Governments and scientific communities are trying their level best to help the masses. This disease which is caused by corona virus majorly attacks the upper respiratory system rendering the human immunity incapacitated and, in some cases, proving fatal. Therefore, it is very much important to identify the infected people quickly and accurately, so that it can be prevented from spread. Early addressal of the symptoms can help to prevent the disease to become severe for all mankind. This calls for the development of a decision-making system to help the medical fraternity for the timely action. This proposed fuzzy based system predicts Covid-19 based on individuals’ symptoms and parameters. It receives input parameters as fever, cough, breathing difficulty, muscle ache, sore throat, travel history, age, medical history in the form of different membership functions and generates one output that predicts the likelihood of a person being infected with COVID-19 using Mamdani fuzzy inference system. The timely prognosis of the disease at home isolation or at the security checks can help the patient to seek the medical treatment as early as possible. Patient case studies, real time observations, cluster cases were studied to create the rule base for FDMS. The results are validated by using real-time individuals test cases on the proposed system which yields 97.2% accuracy, 100% sensitivity and 96.2% specificity.
Fuzzy sets and their variants
Pejman Peykani; Mojtaba Nouri; Farzad Eshghi; Mohammad Khamechian; Hamed Farrokhi-Asl
Abstract
Investment Portfolio Optimization (IPO) is one of the most important problems in the financial area. Also, one of the most important features of financial markets is their embedded uncertainty. Thus, it is essential to propose a novel IPO model that can be employed in the presence of uncertain data. ...
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Investment Portfolio Optimization (IPO) is one of the most important problems in the financial area. Also, one of the most important features of financial markets is their embedded uncertainty. Thus, it is essential to propose a novel IPO model that can be employed in the presence of uncertain data. Accordingly, the main goal of this paper is to propose a novel Fuzzy Multi-Period Multi-Objective Portfolio Optimization (FMPMOPO) model that is capable to be used under data ambiguity and practical constraints including budget constraint, cardinality constraint, and bound constraint. It should be noted that three objectives including terminal wealth, risk, and liquidity as well as practical constraints are considered in proposed FMPMOPO model. Also, the alpha-cut method is employed to deal with fuzzy data. Finally, the proposed Fuzzy Multi-Period Wealth-Risk-Liquidity (FMPWRL) model is implemented in real-world case study from Tehran Stock Exchange (TSE). The experimental results show the applicability and efficacy of the proposed FMPWRL model for fuzzy multi-period multi-objective investment portfolio optimization problem under fuzzy environment.
Fuzzy sets and their variants
Ladji Kane; Moctar Diakite; Souleymane Kane; Hawa Bado; Moussa Konate; Koura Traore
Abstract
Transportation problem is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order to satisfy ...
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Transportation problem is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order to satisfy demands at destinations using available supplies at origins in a crisp environment. In real life situations, the decision maker may not be sure about the precise values of the coefficients belonging to the transportation problem. The aim of this paper is to introduce a formulation of fully fuzzy transportation problem involving trapezoidal fuzzy numbers for the transportation costs and values of supplies and demands. We propose a two-step method for solving fuzzy transportation problem where all of the parameters are represented by triangular fuzzy numbers i.e. two interval transportation problems. Since the proposed approach is based on classical approach it is very easy to understand and to apply on real life transportation problems for the decision makers. To illustrate the proposed approach four application examples are solved. The results show that the proposed method is simpler and computationally more efficient than existing methods in the literature.
Fuzzy sets and their variants
Gurusamy Saravanakumar; S. Tamilselvan; A. Vadivel
Abstract
In this paper, we introduce and study three notions of property in fuzzy topological spaces using quasi-coincidence sense, and we relate to other such notions. Then, we show that all these notions satisfy good extension property. These concepts also satisfy hereditary, productive and projective ...
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In this paper, we introduce and study three notions of property in fuzzy topological spaces using quasi-coincidence sense, and we relate to other such notions. Then, we show that all these notions satisfy good extension property. These concepts also satisfy hereditary, productive and projective properties. We note that all these concepts are preserved under one-one, onto, fuzzy regular open and fuzzy regular continuous mappings. Finally, we discuss initial and final fuzzy topological spaces on our concepts.
Fuzzy sets and their variants
Gia Sirbiladze
Abstract
The Ordered Weighted Averaging (OWA) operator was introduced by Yager [57] to provide a method for aggregating inputs that lie between the max and min operators. In this article two variants of probabilistic extensions the OWA operator-POWA and FPOWA (introduced by Merigo [26] and [27]) are considered ...
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The Ordered Weighted Averaging (OWA) operator was introduced by Yager [57] to provide a method for aggregating inputs that lie between the max and min operators. In this article two variants of probabilistic extensions the OWA operator-POWA and FPOWA (introduced by Merigo [26] and [27]) are considered as a basis of our generalizations in the environment of fuzzy uncertainty (parts II and III of this work), where different monotone measures (fuzzy measure) are used as uncertainty measures instead of the probability measure. For the identification of “classic” OWA and new operators (presented in parts II and III) of aggregations, the Information Structure is introduced where the incomplete available information in the general decision-making system is presented as a condensation of uncertainty measure, imprecision variable and objective function of weights.
Fuzzy sets and their variants
Mazdak Khodadadi-Karimvand; Hadi Shirouyehzad
Abstract
One of the most important issues that organizations have to deal with is the timely identification and detection of risk factors aimed at preventing incidents. Managers’ and engineers’ tendency towards minimizing risk factors in a service, process or design system has obliged them to analyze ...
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One of the most important issues that organizations have to deal with is the timely identification and detection of risk factors aimed at preventing incidents. Managers’ and engineers’ tendency towards minimizing risk factors in a service, process or design system has obliged them to analyze the reliability of such systems in order to minimize the risks and identify the probable errors. Concerning what was just mentioned, a more accurate Failure Mode and Effects Analysis (FMEA) is adopted based on fuzzy logic and fuzzy numbers. Fuzzy TOPSIS is also used to identify, rank, and prioritize error and risk factors. This paper uses FMEA as a risk identification tool. Then, Fuzzy Risk Priority Number (FRPN) is calculated and triangular fuzzy numbers are prioritized through Fuzzy TOPSIS. In order to have a better understanding toward the mentioned concepts, a case study is presented.
Fuzzy sets and their variants
Semiu Ayinla Alayande; Ezekiel Akande; Amanze Egere
Abstract
The purpose of this paper is to describe and present applications of fuzzy logic in analysis of certain neuro-psychopathological symptoms. These symptoms have been linked to conditions relating to occupational hazards. Our method of data analysis which is based on Hamacher operation on picture fuzzy ...
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The purpose of this paper is to describe and present applications of fuzzy logic in analysis of certain neuro-psychopathological symptoms. These symptoms have been linked to conditions relating to occupational hazards. Our method of data analysis which is based on Hamacher operation on picture fuzzy sets is then applied to analyze such occupational hazards. Our result proves to be effective and applicable in medical decision processes especially in situations where such neuro-psychopathological symptoms are detectable by first-aid diagnostic machines.
Fuzzy sets and their variants
Mohammad Ghasempoor Anaraki; Dmitriy S. Vladislav; Mahdi Karbasian; Natalja Osintsev; Victoria Nozick
Abstract
One of the most important issues concerning the designing a supply chain is selecting the supplier. Selecting proper suppliers is one of the most crucial activities of an organization towards the gradual improvement and a promotion in performance. This intricacy is because suppliers fulfil a part of ...
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One of the most important issues concerning the designing a supply chain is selecting the supplier. Selecting proper suppliers is one of the most crucial activities of an organization towards the gradual improvement and a promotion in performance. This intricacy is because suppliers fulfil a part of customer’s expectancy and selecting among them is multi-criteria decision, which needs a systematic and organized approach without which this decision may lead to failure. The purpose of this research is proposing a new method for assessment and rating the suppliers. We have identified several evaluation criteria and attributes; the selection among them was by the Simple Multi-Attribute Rating Technique (SMART) method, then we have specified the connection and the influence of the criteria on each other by DEMATEL method. After that, suppliers were graded by using the Fuzzy Analytical Network Process (FANP) approach and the most efficient one was selected. The innovation of this research is combining the SMART method, DEMATEL method, and Analytical Network Process in Fuzzy state which lead to more exact and efficient results which is proposed for the first time by the researchers of this study.
Fuzzy sets and their variants
Ladji Kane; Hamala Sidibe; Souleymane Kane; Hawa Bado; Moussa Konate; Daouda Diawara; Lassina Diabate
Abstract
Transportation Problem (TP) is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order ...
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Transportation Problem (TP) is an important network structured linear programming problem that arises in several contexts and has deservedly received a great deal of attention in the literature. The central concept in this problem is to find the least total transportation cost of a commodity in order to satisfy demands at destinations using available supplies at origins in a crisp environment. In real life situations, the decision maker may not be sure about the precise values of the coefficients belonging to the transportation problem. The aim of this paper is to introduce a formulation of TP involving Triangular fuzzy numbers for the transportation costs and values of supplies and demands. We propose a two-step method for solving fuzzy transportation problem where all of the parameters are represented by non-negative triangular fuzzy numbers i.e., an Interval Transportation Problems (TPIn) and a Classical Transport Problem (TP). Since the proposed approach is based on classical approach it is very easy to understand and to apply on real life transportation problems for the decision makers. To illustrate the proposed approach two application examples are solved. The results show that the proposed method is simpler and computationally more efficient than existing methods in the literature.
