Recent Advances in Fuzzy Optimization Methods and Models

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 21456

Special Issue Editor

Department of Mathematics, University of the Punjab, Lahore 54590, Pakistan
Interests: fuzzy sets; soft sets; rough sets; decision making; artificial intelligence; pattern recognition; topology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In many real-world situations, you cannot avoid the prevalence of imprecision and uncertainty. For years, the basis for capturing and handling uncertain information had been inadequate before Zadeh, who invented the paradigm of fuzzy sets and founded fuzzy set theory in 1965.

Fuzzy Optimization is a well-known optimization problem in artificial intelligence, computational intelligence, manufacturing and management, so developing general and operable fuzzy optimization methods are necessary for both theory and application.

The need for Fuzzy Optimization theory and methods are manifested in its ability to balance conflicting objectives (goals or interests) where there are many alternative courses of action available to the decision-makers while resources, time and fund are limited.

Fuzzy Optimization is increasingly used in both business and social decision-making. Fuzzy Optimization methods and tools are used for investment strategy, wealth management selection, detection and prevention, direct marketing strategies, predicting customer response, supply chain planning, distribution, routing, scheduling, traffic flow optimization, staff allocation, merchandise optimization, product mix and blending, industrial waste reduction, sustainable energy, raw material process optimization, and product simulation.

Nevertheless, the uncertain multi-objective characteristics of such problems are not yet been explored in-depth and a lot is to be achieved in this direction. Hence, different mathematical models of real-life multi-objective optimization problems can be developed on various uncertain frameworks with special emphasis on combinatorial optimization problems. Optimization of combinatory problems is basically a fundamental issue in various fields, including applied mathematics, computer science, engineering, management, and operations research. Nevertheless, combinatorial problems will have a more realistic sense if the multi-objective nature of the problem can be explored.

The Special Issue emphasises to collect some high-quality papers which develops Fuzzy Optimization models under uncertain environments. Submitted papers should not have been previously published or be currently under consideration for publication elsewhere.

Fuzzy Optimization has long been an important area of management, engineering, and healthcare problems, but has become even more of a focus today due to the emergence of the COVID-19 pandemic.

We invite authors to submit original research articles that propose novel Fuzzy Optimization methods and models including some heuristic and metaheuristic algorithms for practical applications in business, management, manufacturing, logistics, supply chain management, healthcare, and other real-world problems.

Potential topics include but are not limited to the following:

  • Algorithms for fuzzy optimization;
  • Fuzzy Multi-objective decision making;
  • Fuzzy Multi-criteria decision making;
  • Stochastic optimization;
  • Logistics, and supply chain management;
  • Network optimization;
  • Real-time risk assessment and management;
  • Fuzzy optimization in management and engineering;
  • Optimization in sustainable engineering;
  • Uncertain optimization problems;
  • Risk analysis, modelling, sensitivity analysis,  efficiency analysis;
  • Innovative applications of multi-criteria networking.

Dr. Muhammad Riaz
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • algorithms for fuzzy optimization
  • fuzzy multi-objective decision making
  • fuzzy multi-criteria decision making
  • stochastic optimization
  • logistics, and supply chain management
  • network optimization
  • real-time risk assessment and management
  • fuzzy optimization in management and engineering
  • optimization in sustainable engineering
  • uncertain optimization problems
  • risk analysis, modelling, sensitivity analysis, efficiency analysis
  • innovative applications of multi-criteria networking

Published Papers (17 papers)

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Research

28 pages, 2203 KiB  
Article
A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods
by Fahad M. Alqahtani, Mohammed A. Noman, Saad A. Alabdulkarim, Ibrahim Alharkan, Mohammed H. Alhaag and Faisal M. Alessa
Symmetry 2023, 15(11), 1967; https://doi.org/10.3390/sym15111967 - 24 Oct 2023
Viewed by 1344
Abstract
Human errors (HEs) are common problems in manual assembly processes, impacting product quality and resulting in additional costs. Based on expert judgments, this study aims to identify the most significant factors affecting HEs in manual assembly processes and explore the cause-and-effect relationships among [...] Read more.
Human errors (HEs) are common problems in manual assembly processes, impacting product quality and resulting in additional costs. Based on expert judgments, this study aims to identify the most significant factors affecting HEs in manual assembly processes and explore the cause-and-effect relationships among those factors. In order to achieve this objective, a proposed model is constructed using two types of Multi-Criteria Decision-Making (MCDM) techniques. Firstly, using two rounds of the fuzzy Delphi method (FDM), twenty-seven factors with an influence score of 0.7 or higher were found to have a major impact on HEs during manual assembly processes, with at least a 75% consensus among experts. After that, the twenty-seven factors affecting HEs were given to experts in a third round to analyze the cause-and-effect relationships among those factors using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method. In MCDM techniques, symmetry refers to an important property that can be used to find relationships between variables. It is based on the principle that the relative importance or preference between two variables should remain the same regardless of their positions or roles. Therefore, symmetry is a factor that MCDM approaches take into account to ensure that the relationships between variables are accurately represented, leading to more reliable decision-making outcomes. The reliability and normality of the surveying data were examined using the SPSS 22.0 software program. The study results revealed that training level, poor workplace layout, a lack of necessary tools, and experience were the major factors affecting HEs as root causes. Moreover, a failure to address the error-causing problem, unintentional unsafe acts, fatigue, and poor error visual perception were found to be effect (dependent) factors. The findings of this study can help organizations make better-informed decisions on how to reduce worker errors and interest in the factors that contribute to assembly errors and provide a good basis for reaching the quality of final assembled parts. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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27 pages, 1590 KiB  
Article
Solvability Criteria for Uncertain Differential Equations and Their Applicability in an Economic Lot-Size Model with a Type-2 Interval Phenomenon
by Mostafijur Rahaman, Rakibul Haque, Shariful Alam, Sebastian Zupok, Soheil Salahshour, Fariba Azizzadeh and Sankar Prasad Mondal
Symmetry 2023, 15(10), 1883; https://doi.org/10.3390/sym15101883 - 07 Oct 2023
Cited by 1 | Viewed by 774
Abstract
Interval numbers comprise potential fields of application and describe the imprecision brought on by the flexible nature of data between boundaries. The recently added type-2 interval number allows a more thorough understanding of interval numbers. Differential equations are commonly employed in mathematical models [...] Read more.
Interval numbers comprise potential fields of application and describe the imprecision brought on by the flexible nature of data between boundaries. The recently added type-2 interval number allows a more thorough understanding of interval numbers. Differential equations are commonly employed in mathematical models to handle dynamic problems. It is essential to provide theories of differential equations to describe these models in an ambiguous environment controlled by type-2 interval numbers. This study proposes the type-2 interval context solvability requirements for the initial-valued first differential equation. The conditions for the solution’s existence and uniqueness must be met before a brief manifestation of the solution under generalized Hukuhara differentiation occurs. An economic order quantity model analysis in a type-2 interval scenario uses a generalized Hukuhara differentiation approach. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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17 pages, 4890 KiB  
Article
Analysis of the Impact of Big Data and Artificial Intelligence Technology on Supply Chain Management
by Xiao Zeng and Jing Yi
Symmetry 2023, 15(9), 1801; https://doi.org/10.3390/sym15091801 - 21 Sep 2023
Cited by 1 | Viewed by 1409
Abstract
Differentiated production and supply chain management (SCM) areas benefit from the IoT, Big Data, and the data-management capabilities of the AI paradigm. Many businesses have wondered how the arrival of AI will affect planning, organization, optimization, and logistics in the context of SCM. [...] Read more.
Differentiated production and supply chain management (SCM) areas benefit from the IoT, Big Data, and the data-management capabilities of the AI paradigm. Many businesses have wondered how the arrival of AI will affect planning, organization, optimization, and logistics in the context of SCM. Information symmetry is very important here, as maintaining consistency between output and the supply chain is aided by processing and drawing insights from big data. We consider continuous (production) and discontinuous (supply chain) data to satisfy delivery needs to solve the shortage problem. Despite a surplus of output, this article addresses the voluptuous deficiency problem in supply chain administration. This research serves as an overview of AI for SCM practitioners. The report then moves into an in-depth analysis of the most recent studies on and applications of AI in the supply chain industry. This work introduces a novel approach, Incessant Data Processing (IDP), for handling harmonized data on both ends, which should reduce the risk of incorrect results. This processing technique detects shifts in the data stream and uses them to predict future suppressions of demand. Federated learning gathers and analyzes information at several points in the supply chain and is used to spot the shifts. The learning model is educated to forecast further supply chain actions in response to spikes and dips in demand. The entire procedure is simulated using IoT calculations and collected data. An improved prediction accuracy of 9.93%, a reduced analysis time of 9.19%, a reduced data error of 9.77%, and increased alterations of 10.62% are the results of the suggested method. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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28 pages, 653 KiB  
Article
q-Rung Orthopair Fuzzy Archimedean Aggregation Operators: Application in the Site Selection for Software Operating Units
by Mijanur Rahaman Seikh and Utpal Mandal
Symmetry 2023, 15(9), 1680; https://doi.org/10.3390/sym15091680 - 31 Aug 2023
Cited by 3 | Viewed by 762
Abstract
The q-rung orthopair fuzzy (q-ROF) set is an efficient tool for dealing with uncertain and inaccurate data in real-world multi-attribute decision-making (MADM). In MADM, aggregation operators play a significant role. The majority of well-known aggregation operators are formed using algebraic, [...] Read more.
The q-rung orthopair fuzzy (q-ROF) set is an efficient tool for dealing with uncertain and inaccurate data in real-world multi-attribute decision-making (MADM). In MADM, aggregation operators play a significant role. The majority of well-known aggregation operators are formed using algebraic, Einstein, Hamacher, Frank, and Yager t-conorms and t-norms. These existing t-conorms and t-norms are some special cases of Archimedean t-conorms (ATCNs) and Archimedean t-norms (ATNs). Therefore, this article aims to extend the ATCN and ATN operations under the q-ROF environment. In this paper, firstly, we present some new operations for q-ROF sets based on ATCN and ATN. After that, we explore a few desirable characteristics of the suggested operational laws. Then, using these operational laws, we develop q-ROF Archimedean weighted averaging (geometric) operators, q-ROF Archimedean order weighted averaging (geometric) operators, and q-ROF Archimedean hybrid averaging (geometric) operators. Next, we develop a model based on the proposed aggregation operators to handle MADM issues. Finally, we elaborate on a numerical problem about site selection for software operating units to highlight the adaptability and dependability of the developed model. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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17 pages, 418 KiB  
Article
Fuzzy Model Parameter and Structure Optimization Using Analytic, Numerical and Heuristic Approaches
by Joel Artemio Morales-Viscaya, Adán Antonio Alonso-Ramírez, Marco Antonio Castro-Liera, Juan Carlos Gómez-Cortés, David Lazaro-Mata, José Eleazar Peralta-López, Carlos A. Coello Coello, José Enrique Botello-Álvarez and Alejandro Israel Barranco-Gutiérrez
Symmetry 2023, 15(7), 1417; https://doi.org/10.3390/sym15071417 - 14 Jul 2023
Viewed by 1078
Abstract
Fuzzy systems are widely used in most fields of science and engineering, mainly because the models they produce are robust, accurate, easy to evaluate and capture real-world uncertainty better than do the classical alternatives. We propose a new methodology for structure and parameter [...] Read more.
Fuzzy systems are widely used in most fields of science and engineering, mainly because the models they produce are robust, accurate, easy to evaluate and capture real-world uncertainty better than do the classical alternatives. We propose a new methodology for structure and parameter tuning of Takagi–Sugeno–Kang fuzzy models using several optimization techniques. The output parameters are determined analytically, by finding the minimum of the root-mean-square error (RMSE) for a properly defined error function. The membership functions are simplified by considering symmetry and equispacing, to reduce the optimization problem of finding their parameters, and allow it to be carried out using the numerical method of gradient descent. Both algorithms are fast enough to finally implement a strategy based on the hill climbing approach to finding the optimal structure (number and type of membership functions) of the fuzzy system. The effectiveness of the proposed strategy is shown by comparing its performance, using four case studies found in current relevant works, to the popular adaptive network-based fuzzy inference system (ANFIS), and to other recently published strategies based on evolutionary fuzzy models. In terms of the RMSE, performance was at least 28% better in all case studies. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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26 pages, 2657 KiB  
Article
A Decision-Making Approach to Optimize COVID-19 Treatment Strategy under a Conjunctive Complex Fuzzy Environment
by Muhammad Iftikhar Faraz, Ghaliah Alhamzi, Aneeza Imtiaz, Ibtisam Masmali, Umer Shuaib, Abdul Razaq and Asima Razzaque
Symmetry 2023, 15(7), 1370; https://doi.org/10.3390/sym15071370 - 05 Jul 2023
Cited by 1 | Viewed by 813
Abstract
Symmetry is a key part of the study of basic forces and particles, as well as the creation of mathematical models that help scientists in various scientific disciplines understand complex events. Scientists can figure out what a system is made of and how [...] Read more.
Symmetry is a key part of the study of basic forces and particles, as well as the creation of mathematical models that help scientists in various scientific disciplines understand complex events. Scientists can figure out what a system is made of and how it works by looking at its symmetry. They can then use this information to make predictions and create new materials and technologies. Humanity has conquered many once-fatal diseases due to medical research and technological advancements. Although this progress is encouraging, there are still a great many areas that require continual human efforts. An effort is made in this article to choose the best treatment strategy to completely manage the pandemic of COVID-19 under conjunctive complex fuzzy knowledge. In this paper, the concept of conjunctive complex fuzzy relations is presented and numerous set theoretical aspects of this phenomenon are established. The investigation of this ideology is further expanded to describe different sorts of essential structural conjunctive complex fuzzy relations. Matrix and graphical representations of the formation of these newly specified relations are also provided. Moreover, this concept has been successfully employed to provide a therapy strategy for a rapid recovery from COVID-19. Furthermore, a comparative analysis is conducted to demonstrate the validity and applicability of the suggested approaches compared to existing methods. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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31 pages, 1238 KiB  
Article
Prioritization of Thermal Energy Storage Techniques Using TOPSIS Method Based on Correlation Coefficient for Interval-Valued Intuitionistic Fuzzy Hypersoft Set
by Rana Muhammad Zulqarnain, Wen-Xiu Ma, Imran Siddique, Alhanouf Alburaikan, Hamiden Abd El-Wahed Khalifa and Agaeb Mahal Alanzi
Symmetry 2023, 15(3), 615; https://doi.org/10.3390/sym15030615 - 28 Feb 2023
Cited by 3 | Viewed by 1011
Abstract
The correlation between two disparate variables conquers a significant habitation in statistics. The concept of correlation coefficient (CC) is one of the well-known indicators, but it is not used in interval-valued intuitionistic fuzzy hypersoft set (IVIFHSS) information. It is a generalization of interval-valued [...] Read more.
The correlation between two disparate variables conquers a significant habitation in statistics. The concept of correlation coefficient (CC) is one of the well-known indicators, but it is not used in interval-valued intuitionistic fuzzy hypersoft set (IVIFHSS) information. It is a generalization of interval-valued intuitionistic fuzzy soft sets and a refined extension of intuitionistic fuzzy hypersoft sets. However, using the CC and weighted correlation coefficient (WCC) has not yet been explored for IVIFHSS information. The core objective of this research is to present the correlation coefficient (CC) and weighted correlation coefficient (WCC) for interval-valued intuitionistic fuzzy hypersoft sets (IVIFHSS) and their mandatory properties. A prioritization technique for order preference by similarity to the ideal solution (TOPSIS) is developed based on proposed correlation measures. To ensure the symmetry of the developed scheme, we consider mathematical clarifications of correlation contractions. Based on assessments, it conceded vibrant multi-attribute decision-making (MADM) methodology with the most substantial significance. In addition, a statistical illustration is designated to regulate the operative usage of a decision-making configuration in thermal energy storage techniques. The productivity of the advocated algorithm is more reliable than existing replicas to control the favorable configurations of the premeditated study. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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40 pages, 815 KiB  
Article
An Optimization Strategy for MADM Framework with Confidence Level Aggregation Operators under Probabilistic Neutrosophic Hesitant Fuzzy Rough Environment
by Muhammad Kamran, Rashad Ismail, Esmail Hassan Abdullatif Al-Sabri, Nadeem Salamat, Muhammad Farman and Shahzaib Ashraf
Symmetry 2023, 15(3), 578; https://doi.org/10.3390/sym15030578 - 22 Feb 2023
Cited by 10 | Viewed by 1034
Abstract
In this research, we first offer unique notions of averaging and geometric aggregation operators with confidence level by employing a probabilistic neutrosophic hesitant fuzzy rough framework. Then, we look into other descriptions of the suggested operators, such as idempotency, boundedness, and monotonicity. Additionally, [...] Read more.
In this research, we first offer unique notions of averaging and geometric aggregation operators with confidence level by employing a probabilistic neutrosophic hesitant fuzzy rough framework. Then, we look into other descriptions of the suggested operators, such as idempotency, boundedness, and monotonicity. Additionally, for the derived operators, we establish the score and accuracy functions. We also provide a novel approach to assessing the selection procedure for smart medical devices (SMDs). The selection criteria for SMDs are quite complex, which is the most noteworthy feature of this investigation. It is suggested that these processes be simulated using a method utilizing a hesitant fuzzy set, a rough set, and a probabilistic single-valued neutrosophics set. The proposed approach is employed in the decision-making process, while taking into consideration the decision-makers’ (DMs’) level of confidence in the data they have obtained in order to deal with ambiguity, incomplete data, and uncertainty in lower and upper approximations. The major goal was to outline the issue’s complexities in order to pique interest among experts in the health care sector and encourage them to evaluate SMDs using various evaluation standards. The analysis of the technique’s outcomes demonstrated that the rankings and the results themselves were adequate and trustworthy. The effectiveness of our suggested improvements is also demonstrated through a symmetrical analysis. The symmetry behavior shows that the current techniques address more complex and advanced data. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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20 pages, 312 KiB  
Article
Some Results on Submodules Using (μ,ν,ω)-Single-Valued Neutrosophic Environment
by Muhammad Shazib Hameed, Esmail Hassan Abdullatif Al-Sabri, Zaheer Ahmad, Shahbaz Ali and Muhammad Usman Ghani
Symmetry 2023, 15(1), 247; https://doi.org/10.3390/sym15010247 - 16 Jan 2023
Cited by 2 | Viewed by 1093
Abstract
The use of a single-valued neutrosophic set (svns) makes it much easier to manage situations in which one must deal with incorrect, unexpected, susceptible, faulty, vulnerable, and complicated information. This is a result of the fact that the specific forms of material being [...] Read more.
The use of a single-valued neutrosophic set (svns) makes it much easier to manage situations in which one must deal with incorrect, unexpected, susceptible, faulty, vulnerable, and complicated information. This is a result of the fact that the specific forms of material being discussed here are more likely to include errors. This new theory has directly contributed to the expansion of both the concept of fuzzy sets and intuitionistic fuzzy sets, both of which have experienced additional development as a direct consequence of the creation of this new theory. In svns, indeterminacy is correctly assessed in a way that is both subtle and unambiguous. Furthermore, membership in the truth, indeterminacy, and falsity are all completely independent of one another. In the context of algebraic analysis, certain binary operations may be regarded as interacting with algebraic modules. These modules have pervasive and complicated designs. Modules may be put to use in a wide variety of different applications. Modules have applications in a diverse range of industries and market subsets due to their adaptability and versatility. Under the umbrella of the triplet (μ,ν,ω) structure, we investigate the concept of svns and establish a relationship between it and the single-valued neutrosophic module and the single-valued neutrosophic submodule, respectively. The purpose of this study is to gain an understanding of the algebraic structures of single-valued neutrosophic submodules under the triplet structure of a classical module and to improve the validity of this method by analyzing a variety of important facets. In this article, numerous symmetrical features of modules are also investigated, which demonstrates the usefulness and practicality of these qualities. The results of this research will allow for the successful completion of both of these objectives. The tactics that we have devised for use in this article are more applicable to a wide variety of situations than those that have been used in the past. Fuzzy sets, intuitionistic fuzzy sets, and neutrosophic sets are some of the tactics that fall under this category. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
20 pages, 611 KiB  
Article
Innovative CODAS Algorithm for q-Rung Orthopair Fuzzy Information and Cancer Risk Assessment
by Rukhsana Kausar, Hafiz Muhammad Athar Farid, Muhammad Riaz and Nazmiye Gonul Bilgin
Symmetry 2023, 15(1), 205; https://doi.org/10.3390/sym15010205 - 10 Jan 2023
Cited by 6 | Viewed by 1148
Abstract
Due to insufficient healthcare facilities for the fight against cancer, a large percentage of individuals die. Utilizing computational tools inside the health and medical system helps to minimize fatalities. Timely cancer detection enhances the likelihood of effective therapy. Cancer risk assessment is important [...] Read more.
Due to insufficient healthcare facilities for the fight against cancer, a large percentage of individuals die. Utilizing computational tools inside the health and medical system helps to minimize fatalities. Timely cancer detection enhances the likelihood of effective therapy. Cancer risk assessment is important for legal and regulatory reasons, for cancer prevention, and to avoid the risks. The approach for assessing cancer risk based on the q-rung orthopair fuzzy set (q-ROFS) is described. The technique is predicated on a multifactor evaluation of the likelihood of a cancerous. q-ROFS is a robust approach for modeling uncertainties in multicriteria decision making (MCDM). The combinative distance-based assessment (CODAS) technique integrates two separate approaches, namely the “simple additive weighting” (SAW) method and the “weighted product method (WPM)”. In this study, the CODAS approach is extended to the q-rung orthopair fuzzy framework with application to cancer risk assessment. Additionally, the symmetry of the optimal decision in cancer risk assessment is carried out by a comparison analysis of the suggested model with some existing models. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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18 pages, 313 KiB  
Article
Extension of a Unique Solution in Generalized Neutrosophic Cone Metric Spaces
by Umar Ishtiaq, Muhammad Asif, Aftab Hussain, Khaleel Ahmad, Iqra Saleem and Hamed Al Sulami
Symmetry 2023, 15(1), 94; https://doi.org/10.3390/sym15010094 - 29 Dec 2022
Viewed by 957
Abstract
In order to solve issues that arise in various branches of mathematical analysis, such as split feasibility problems, variational inequality problems, nonlinear optimization issues, equilibrium problems, complementarity issues, selection and matching problems, and issues proving the existence of solutions to integral and differential [...] Read more.
In order to solve issues that arise in various branches of mathematical analysis, such as split feasibility problems, variational inequality problems, nonlinear optimization issues, equilibrium problems, complementarity issues, selection and matching problems, and issues proving the existence of solutions to integral and differential equations, fixed point theory provides vital tools. In this study, we discuss topological structure and several fixed-point theorems in the context of generalized neutrosophic cone metric spaces. In these spaces, the symmetric properties play an important role. We examine the existence and a uniqueness of a solution by utilizing new types of contraction mappings under some circumstances. We provide an example in which we show the existence and a uniqueness of a solution by utilizing our main result. These results are more generalized in the existing literature. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
20 pages, 432 KiB  
Article
A Theoretical Development of Cubic Pythagorean Fuzzy Soft Set with Its Application in Multi-Attribute Decision Making
by Muhammad Saeed, Muhammad Haris Saeed, Rimsha Shafaqat, Salvatore Sessa, Umar Ishtiaq and Ferdinando di Martino
Symmetry 2022, 14(12), 2639; https://doi.org/10.3390/sym14122639 - 13 Dec 2022
Cited by 5 | Viewed by 1435
Abstract
Scientific progression has allowed researchers to develop novel and innovative ways to deal with uncertainty in data, allowing for the development of more precise and accurate data representation models. This paper aims to extend an already reported concept of Cubic Pythagorean fuzzy set [...] Read more.
Scientific progression has allowed researchers to develop novel and innovative ways to deal with uncertainty in data, allowing for the development of more precise and accurate data representation models. This paper aims to extend an already reported concept of Cubic Pythagorean fuzzy set to Cubic Pythagorean Fuzzy Soft Set (CPFSs) as it incorporates both interval-valued Pythagorean fuzzy sets (IVPFS) and Pythagorean fuzzy sets (PFS) at the same time, providing a more targeted approach to deal with uncertainty. This hybrid structure can better handle data in comparison to the ones in the literature by having the characteristics of PFS and soft sets, leading to a more targeted approach to handle attributes in decision-making studies. In this study, we defined various internals and externals of CPFSs, set operators, aggregation operators, and developed an algorithm based on distance measures for (CPFSs), which are applied in a disease diagnostic decision-making problem. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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24 pages, 445 KiB  
Article
Confidence Levels Complex q-Rung Orthopair Fuzzy Aggregation Operators and Its Application in Decision Making Problem
by Muhammad Qiyas, Muhammad Naeem and Neelam Khan
Symmetry 2022, 14(12), 2638; https://doi.org/10.3390/sym14122638 - 13 Dec 2022
Cited by 3 | Viewed by 1310
Abstract
The theory investigated in this analysis is substantially more suitable for evaluating the dilemmas in real life to manage complicated, risk-illustrating, and asymmetric information. The complex Pythagorean fuzzy set is expanded upon by the complex q-rung orthopair fuzzy set (Cq-ROFS). They stand out [...] Read more.
The theory investigated in this analysis is substantially more suitable for evaluating the dilemmas in real life to manage complicated, risk-illustrating, and asymmetric information. The complex Pythagorean fuzzy set is expanded upon by the complex q-rung orthopair fuzzy set (Cq-ROFS). They stand out by having a qth power of the real part of the complex-valued membership degree and a qth power of the real part and imaginary part of the complex-valued non-membership degree that is equal to or less than 1. We define the comparison method for two complex q-rung orthopair fuzzy numbers as well as the score and accuracy functions (Cq-ROFNs). Some averaging and geometric aggregation operators are examined using the Cq-ROFSs operational rules. Additionally, their main characteristics have been fully illustrated. Based on the suggested operators, we give a novel approach to solve the multi-attribute group decision-making issues that arise in environmental contexts. Making the best choice when there are asymmetric types of information offered by different specialists is the major goal of this work. Finally, we used real data to choose an ideal extinguisher from a variety of options in order to show the effectiveness of our decision-making technique. The effectiveness of the experimental outcomes compared to earlier research efforts is then shown by comparing them to other methods. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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25 pages, 1966 KiB  
Article
Gas Cooled Graphite Moderated and Pressurized Water Reactor the Optimal Choice for Nuclear Power Plants Based on a New Group Decision-Making Technique
by Mohammed M. Khalaf, Rashad Ismail, Mohammed M. Ali Al-Shamiri and Abdelazeem M. Abdelwahab
Symmetry 2022, 14(12), 2621; https://doi.org/10.3390/sym14122621 - 11 Dec 2022
Viewed by 995
Abstract
The aim of this work is to introduce the novel concept of an m-polar fuzzy soft set, including various types of algorithms and their fundamental operations. We created mathematical modeling to analyze operational rules and discuss the advantages, disadvantages, and natural aspects of [...] Read more.
The aim of this work is to introduce the novel concept of an m-polar fuzzy soft set, including various types of algorithms and their fundamental operations. We created mathematical modeling to analyze operational rules and discuss the advantages, disadvantages, and natural aspects of algorithms for six types of nuclear power plants. It has been determined that emerging trends and the benefits of algorithms are increasing step by step. The suggested modeling with an m-polar fuzzy soft set is integrated into the fuzzy mean environment to analyze the effect of the correlation between decision factors and decision results without an excessive duty cycle, thus minimizing energy use and other adverse effects. Based on a new group decision-making technique considering an asymmetric weight vector, we proved that Gas Cooled, Graphite-Moderated, and Pressurized Water Reactors are the optimal choices for nuclear power plants. In the end, a numerical illustration is provided for selecting the best photo to demonstrate the use of the generated technique and to exhibit its adequacy. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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40 pages, 4347 KiB  
Article
Cancer Therapy Assessment Accounting for Heterogeneity Using q-Rung Picture Fuzzy Dynamic Aggregation Approach
by Rukhsana Kausar, Hafiz Muhammad Athar Farid, Muhammad Riaz and Darko Božanić
Symmetry 2022, 14(12), 2538; https://doi.org/10.3390/sym14122538 - 30 Nov 2022
Cited by 6 | Viewed by 1151
Abstract
Due to the fact that there is no symmetry in the division of cancer cells, it is important to consider this asymmetrical behavior. Because of this heterogeneity during any therapy, not every cancer cell that is killed only is abolished, which is sensitive [...] Read more.
Due to the fact that there is no symmetry in the division of cancer cells, it is important to consider this asymmetrical behavior. Because of this heterogeneity during any therapy, not every cancer cell that is killed only is abolished, which is sensitive to the particular treatment chosen. Mathematical models that describe these pathways are critical for predicting cancer cell proliferation behavior. The literature on the mathematical modeling of cancer onset, growth, and metastasis is extensive. Both deterministic and stochastic factors were used to develop mathematical models to mimic the development rate of cancer cells. We focus on the cell’s heterogeneity in our model so that the cells generally responsible for spreading cancer, which are called stem cells, can be killed. Aggregation operators (AOs) play an important role in decision making, especially when there are several competing factors. A key issue in the case of uncertain data is to develop appropriate solutions for the aggregation process. We presented two novel Einstein AOs: q-rung picture fuzzy dynamic Einstein weighted averaging (q-RPFDEWA) operator and q-rung picture fuzzy dynamic Einstein weighted geometric (q-RPFDEWG) operator. Several enticing aspects of these AOs are thoroughly discussed. Furthermore, we provide a method for dealing with multi-period decision-making (MPDM) issues by applying optimal solutions. A numerical example is presented to explain how the recommended technique can be used in cancer therapy assessment. Authenticity analysis is also presented to demonstrate the efficacy of the proposed technique. The suggested AOs and decision-making methodologies are generally applicable in real-world multi-stage and dynamic decision analysis. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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16 pages, 3536 KiB  
Article
Fermatean Neutrosophic Topological Spaces and an Application of Neutrosophic Kano Method
by Nazmiye Gonul Bilgin, Dragan Pamučar and Muhammad Riaz
Symmetry 2022, 14(11), 2442; https://doi.org/10.3390/sym14112442 - 17 Nov 2022
Cited by 3 | Viewed by 1491
Abstract
The main objective of this paper is to redefine the concept of Fermatean neutrosophic sets as well as to introduce topological structure on Fermatean neutrosophic sets. The idea of Fermatean neutrosophic sets is the hybrid model of Fermatean fuzzy sets and neutrosophic sets [...] Read more.
The main objective of this paper is to redefine the concept of Fermatean neutrosophic sets as well as to introduce topological structure on Fermatean neutrosophic sets. The idea of Fermatean neutrosophic sets is the hybrid model of Fermatean fuzzy sets and neutrosophic sets to utilize key features of these structures. Topological data analysis for indeterminate and uncertain information is a rapidly developing field. Motivated by this recent trend, the idea of Fermatean neutrosophic topology is proposed, which is an extension of neutrosophic topology and Fermatean fuzzy topology. Some fundamental properties of Fermatean neutrosophic topology are explored and related results are investigated. Certain properties provided in the classical topological space that may not be valid in this space is one of the factors that makes the study important. Moreover, an application is made for the problem of seeking reasonable solutions to customer expectations by using the neutrosophic Kano method, which is an interesting illustration of neutrosophic decision making. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
28 pages, 427 KiB  
Article
An Optimization Approach with Single-Valued Neutrosophic Hesitant Fuzzy Dombi Aggregation Operators
by Sania Batool, Masooma Raza Hashmi, Muhammad Riaz, Florentin Smarandache, Dragan Pamucar and Dejan Spasic
Symmetry 2022, 14(11), 2271; https://doi.org/10.3390/sym14112271 - 29 Oct 2022
Cited by 5 | Viewed by 1066
Abstract
Using the strength of a single-valued neutrosophic set (SVNS) with the flexibility of a hesitant fuzzy set (HFS) yields a robust model named the single-valued neutrosophic hesitant fuzzy set (SVNHFS). Due to the ability to utilize three independent indexes (truthness, indeterminacy, and falsity), [...] Read more.
Using the strength of a single-valued neutrosophic set (SVNS) with the flexibility of a hesitant fuzzy set (HFS) yields a robust model named the single-valued neutrosophic hesitant fuzzy set (SVNHFS). Due to the ability to utilize three independent indexes (truthness, indeterminacy, and falsity), an SVNHFS is an efficient model for optimization and computational intelligence (CI) as well as an intelligent decision support system (IDSS). Taking advantage of the flexibility of operational parameters in Dombi’s t-norm and t-conorm operations, new aggregation operators (AOs) are proposed, which are named the SVN fuzzy Dombi weighted averaging (SVNHFDWA) operator, SVN hesitant fuzzy Dombi ordered weighted averaging (SVNHFDOWA) operator, SVN hesitant fuzzy Dombi hybrid averaging (SVNHFDHWA) operator, SVN hesitant fuzzy Dombi weighted geometric (SVNHFDWG) operator, SVN hesitant fuzzy Dombi ordered weighted geometric (SVNHFDOWG) operator as well as SVN hesitant fuzzy Dombi hybrid weighted geometric (SVNHFDHWG) operator. The efficiency of these AOs is investigated in order to determine the best option using SVN hesitant fuzzy numbers (SVNHFNs) in an IDSS. Additionally, a practical application of SVNHFDWA and SVNHFDWG is also presented to examine symmetrical analysis in the selection of wireless charging station for vehicles. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Optimization Methods and Models)
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