Fuzzy sets and their variants
Mhalla Anis; Simon Collart Dutilleul
Abstract
The scope of the presented work is devoted to the monitoring of transport railway networks. These systems have robustness to temporal perturbations. The major paper's contribution is a fuzzy filtering of sensor signals incorporating robustness parameters. This novel concept combines a conventional sensor ...
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The scope of the presented work is devoted to the monitoring of transport railway networks. These systems have robustness to temporal perturbations. The major paper's contribution is a fuzzy filtering of sensor signals incorporating robustness parameters. This novel concept combines a conventional sensor signal filter mechanism and fuzzy logic principles. The strengths of these two techniques are leveraged to prevent control freezing and the fuzzy systems' ability to handle inaccurate information by employing fuzzy rules. Lastly, to prove the efficiency and the accuracy of the newly developed approach, an example is shown. The findings reveal that the fuzzy logic allows to maintain the travel process in a degraded mode, while ensuring the traffic quality and customers safety through the incorporation of expert knowledge.
Fuzzy sets and their variants
Sapan Kumar Das; Indrani Maiti; RAJEEV PRASAD; Surapati Pramanik; Tarni Mandal
Abstract
The prediction of a real-life problem like in industrial sector or health sector the outcome is impossible or sometimes it is difficult. Due to high information uncertainty and complicated influencing factors of industrial sector, the traditional data-driven prediction approaches can hardly reflect the ...
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The prediction of a real-life problem like in industrial sector or health sector the outcome is impossible or sometimes it is difficult. Due to high information uncertainty and complicated influencing factors of industrial sector, the traditional data-driven prediction approaches can hardly reflect the real changes in practical situation. Fuzzy programming is a powerful prediction reasoning and risk assessment model for uncertain environment. This article mainly explores and applies a modified form of fuzzy programming; namely Fuzzy Linear Fractional Programming Problem (FLFPP) having the coefficients of the objectives and constraints as triangular fuzzy numbers (TFNs). The FLFPP is converted into an equivalent crisp multi-objective linear fractional programming problem (MOLFPP) and solved individually to associate an aspiration level to it. Then by applying fuzzy goal programming (FGP) technique the maximum degree of each membership goal is obtained by minimizing the negative deviational variables. We carry out two industrial application simulations in a hypothetical industrial scenario. Our study shows that the proposed model is practical and applicable to the uncertain practical environment to realize the prediction and the obtained results are compared with that of the existing methods.
Fuzzy sets and their variants
Kamala Rafig Aliyeva
Abstract
Group decision making in capital investment involves a collaborative process where multiple stakeholders contribute their perspectives, insights, and expertise to evaluate investment opportunities and make informed decisions. The practical and methodological aims of this process can vary depending on ...
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Group decision making in capital investment involves a collaborative process where multiple stakeholders contribute their perspectives, insights, and expertise to evaluate investment opportunities and make informed decisions. The practical and methodological aims of this process can vary depending on the organization's goals, industry, and market conditions. Conducting research on capital investment group decision making is motivated by several factors such as optimizing investment decisions, enhancing performance, managing risk, adapting to changing conditions, building knowledge and expertise. The investment decision relates to the distribution of financial resources. Investors select the most appropriate investment opportunities based on risk profiles, investment aims and expected returns. Fuzzy multicriteria group decision making in capital investment extends the traditional decision-making process to accommodate multiple criteria that are often uncertain, vague, or subjective in nature. The goal of this paper is to suggest a technique known as the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (fuzzy TOPSIS) for group decision making about investment in the respective vehicle. Fuzzy TOPSIS technique represents a decision for experts, which is multi-criteria and includes an aggregated decision-making process. This paper shows the application of this method when choosing the best alternative, considering the choice of vehicle.
Fuzzy sets and their variants
Wencun Wang; Jun Yao; Di Zhao; Can Huang
Abstract
This study investigates integrating and optimizing an intelligent rural management system leveraging advanced technologies, including the Internet of Things (IoT), blockchain, and social networks. Initially, it identifies and scrutinizes prevailing issues in rural development processes, emphasizing the ...
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This study investigates integrating and optimizing an intelligent rural management system leveraging advanced technologies, including the Internet of Things (IoT), blockchain, and social networks. Initially, it identifies and scrutinizes prevailing issues in rural development processes, emphasizing the role of rural cultural dissemination, with a specific focus on the impact of social networks. Subsequently, by incorporating fuzzy set theory and adopting an enhanced blockchain consensus algorithm—the Byzantine Fault Tolerance (BFT) algorithm— a comprehensive rural management system is established, combining fuzzy sets and blockchain. Lastly, an intelligent traffic management system is developed to address logistics and distribution challenges in rural revitalization, facilitating efficient interurban delivery. The system automatically invokes the Matlab dynamic link library and employs a hybrid genetic algorithm to plan delivery routes. This study presents key findings on implementing an intelligent rural management system incorporating fuzzy sets, blockchain, and IoT technology. The system notably enhances transparency and traceability in agricultural production and supply chain processes, optimizes logistics and distribution efficiency, and reduces operational costs through intelligent management techniques. Additionally, the integrated application significantly bolsters consumer trust in the quality and safety of agricultural products, leading to heightened overall user satisfaction.
Fuzzy sets and their variants
Sahabul Alam; Joydeep Kundu; Shivnath Ghosh; Arindam Dey
Abstract
Unmanned Aerial Vehicles (UAVs) bring both potential and difficulties for emergency applications, including packet loss and changes in network topology. UAVs are also quickly taking up a sizable portion of the airspace, allowing Flying Ad-hoc NETworks (FANETs) to conduct effective ad hoc missions. Therefore, ...
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Unmanned Aerial Vehicles (UAVs) bring both potential and difficulties for emergency applications, including packet loss and changes in network topology. UAVs are also quickly taking up a sizable portion of the airspace, allowing Flying Ad-hoc NETworks (FANETs) to conduct effective ad hoc missions. Therefore, building routing protocols for FANETs is difficult due to flight restrictions and changing topology. To solve these problems, a bio-inspired route selection technique is proposed for FANET. A combined trustworthy and bioinspired-based transmission strategy is developed as a result of the growing need for dynamic and adaptable communications in FANETs. The fitness theory is used to assess direct trust and evaluate credibility and activity to estimate indirect trust. In particular, assessing UAV behavior is still a crucial problem in this field. It recommends fuzzy logic, one of the most widely utilized techniques for trusted route computing, for this purpose. Fuzzy logic can manage complicated settings by classifying nodes based on various criteria. This method combines geocaching and unicasting, anticipating the location of intermediate UAVs using 3-D estimates. This method guarantees resilience, dependability, and an extended path lifetime, improving FANET performance noticeably. Two primary features of FANETs that shorten the route lifetime must be accommodated in routing. First, the collaborative nature necessitates communication and coordination between the flying nodes, which uses a lot of energy. Second, the flying nodes' highly dynamic mobility pattern in 3D space may cause link disconnection because of their potential dispersion. Using ant colony optimization, it employs trusted leader drone selection within the cluster and safe routing among leaders. a fuzzy‐based UAV behavior analytics is presented for trust management in FANETs. Compared to existing protocols, the simulated results demonstrate improvements in delay routing overhead in FANET.
Fuzzy sets and their variants
Abouzar Sheikhi; Mohammad Javad Ebadi
Abstract
In this paper, we present a novel method for solving Fractional Transportation Problems (FTPs) with fuzzy numbers using a ranking function. The proposed method introduces a transformation technique that converts an FTP with fuzzy numbers into an FTP with crisp numbers by employing the robust ranking ...
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In this paper, we present a novel method for solving Fractional Transportation Problems (FTPs) with fuzzy numbers using a ranking function. The proposed method introduces a transformation technique that converts an FTP with fuzzy numbers into an FTP with crisp numbers by employing the robust ranking technique. Subsequently, we formulate two transportation problems, one for maximization and another for minimization, based on the given FTP. The optimal solution for the original FTP is then derived by leveraging the solutions obtained for the formulated transportation problems. By optimizing these single-objective transport problems, our method provides decision-makers with the ability to make satisfactory managerial decisions and evaluate economic operations when confronted with logistic problems involving fractional transportation. To demonstrate the effectiveness of the proposed approach, we present several illustrative examples that showcase its practical application and efficiency.
Fuzzy sets and their variants
Sivasankar Shanmugam; Thirumal Perumal Aishwarya; Nagesh Shreya
Abstract
In communication networks, strong connectivity between nodes is critical. The failure of strong connectivity between nodes may jeopardize the network’s stability. In fuzzy graphs, various dominating sets using strong edges are identified to avoid network stability. In this paper, the concept of ...
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In communication networks, strong connectivity between nodes is critical. The failure of strong connectivity between nodes may jeopardize the network’s stability. In fuzzy graphs, various dominating sets using strong edges are identified to avoid network stability. In this paper, the concept of bridge domination set and bridge domination number in fuzzy graphs is introduced. A few prominent properties of bridge domination numbers are chosen and analyzed using relevant examples. The bridge domination number of fuzzy trees, constant fuzzy cycles, and complete fuzzy and bipartite fuzzy graphs are identified. The use of bridge domination in a partial mesh topology to ensure network continuity is demonstrated in the event of a node failure.
Fuzzy sets and their variants
Abolfazl Rezaei; Mohammad Hemati
Abstract
Today, most manufacturing and service companies adopt a customer-oriented approach to take into account employee needs and expectations as a strategic principle for sustainability and success in a competitive market. Meanwhile, Sengeh argues that “many of the best ideas and strategies will not ...
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Today, most manufacturing and service companies adopt a customer-oriented approach to take into account employee needs and expectations as a strategic principle for sustainability and success in a competitive market. Meanwhile, Sengeh argues that “many of the best ideas and strategies will not be realized due to the conflict between new ideas and managers’ subjective model, rather than the management weakness”. On the other hand, managers’ decisions based on self-developed rules can suffer all kinds of biases. As Bierzman explains: “managers’ mental heuristic rules lead to weak analysis of information, inappropriate weighting of the various data, and an investigation of few alternatives for decision-making, which can lead to systematic errors and common biases in the decision”. Addressing the existing gap between managers’ subjective perceptions of employees and employees’ self-perceptions, the present study aims to present a new systematic approach with a combination of Delphi, Kano and AHP methods in an attempt to explain managers’ mental paradigms in Abadan Oil Refinary Company as one of the elading ones in the Middle East. The statistical population of the study consists of 18 experienced managers (using snowball method) and 203 employees at Abadan’s Oil Refinery (using the Cochran formula). The validity and reliability of the questionnaire were also confirmed using Kendall’s Correlation Coefficient, Cronbach’s Alpha coefficient, and Gogus and Butcher’s Incompatibility Rate. First, needs were determined from the views of the experts using the Fuzzy Delphi method, and then, Kano’s non-linear model and Alpha-cut (α-Cut) method were used to classify 21 components as basic, performance, and excitement needs. In the end, the needs have been ranked using the Fuzzy AHP method. The results indicated that the proposed method was effectively successful in reducing biases, vagueness, and possible inconsistencies in managers' decisions and judgments. Overall, the method presented insights on the significance of future strategic decisions to achieve sustainable competitive advantages and to increase employee satisfaction while categorizing the needs optimally as confirmed and welcomed by decision-making experts.
Fuzzy sets and their variants
Muhammad Waseem Asghar; Khushdil Ahmad
Abstract
In this paper, we define the term " 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 the η-fuzzy normal subgroup and the quotient group with respect to the ...
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In this paper, we define the term " 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 the η-fuzzy normal subgroup and the 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
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 ...
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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 with a cyclic group of order of an m power of two for, which n >5.
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 slightly 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
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.
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.