Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.5
2.4
Journals
Mathematics
Special Issues
Fuzzy Sets and Soft Computing
share announcement

Fuzzy Sets and Soft Computing

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 38929

Special Issue Editors

Prof. Dr. Gustavo Santos-García

E-Mail Website
Guest Editor
Facultad de Economía y Empresa and Multidisciplinary Institute of Enterprise (IME), Universidad de Salamanca, 37007 Salamanca, Spain
Interests: artificial Intelligence; soft computing; rewriting logic; computational biology; decision theory
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. José Carlos R. Alcantud

E-Mail Website
Guest Editor
BORDA Research Unit and Multidisciplinary Institute of Enterprise (IME), University of Salamanca, 37007 Salamanca, Spain
Interests: decision theory; social choice; mathematical economics; fuzzy set theory
Special Issues, Collections and Topics in MDPI journals
Dr. Enrico Marchioni

E-Mail Website
Guest Editor
Department of Electronics and Computer Science, University of Southampton, Southampton, UK
Interests: game theory; reasoning under uncertainty; mathematical logic

Special Issue Information

Dear Colleagues

John McCarthy coined the term Artificial Intelligence in the 1950s. From his point of view, AI is not about imitating human reasoning and the human way of solving problems, but about finding the essence of abstract reasoning and problem solving. At present, IA focuses on the study of intelligent agents, that is, of autonomous entities capable of perceiving their environment and which, like humans, have the capacity to act so as to optimize their objectives.

Soft computing is a branch of Artificial Intelligence that studies the techniques used in the resolution of problems that handle incomplete, uncertain, and/or inaccurate information. Fuzzy sets are fundamental in the theory of uncertainty. Fuzzy sets and soft computing provide numerous theoretical and practical tools for complex linguistic and numerical modeling applications.

The purpose of this Special Issue is to gather a collection of articles on the latest research and developments in this field of research which includes but is not limited to topics such as: automated reasoning and inference, heuristic search, natural language processing, applications in medical sciences and bioinformatics, knowledge representation, extensions and generalizations of fuzzy sets, aggregation operations, information content measures, preference modeling and multicriteria evaluation, and reasoning under uncertainty.

Prof. Dr. Gustavo Santos-García 
Prof. Dr. José Carlos R. Alcantud
Dr. Enrico Marchioni
Guest Editors

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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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

  • Mathematical logic and mathematical foundation
  • Foundations of soft computing
  • Fuzzy set theory
  • Reasoning under uncertainty
  • Extensions and generalizations of fuzzy sets
  • Knowledge representation
  • Web-based intelligence
  • Heuristic search in soft computing
  • Soft computing applications in medical sciences and bioinformatics
  • Mathematical and computational biology

Published Papers (16 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

26 pages, 422 KiB  
Article
Some New Concepts Related to Integral Operators and Inequalities on Coordinates in Fuzzy Fractional Calculus
by Muhammad Bilal Khan, Gustavo Santos-García, Hatim Ghazi Zaini, Savin Treanță and Mohamed S. Soliman
Mathematics 2022, 10(4), 534; https://0-doi-org.brum.beds.ac.uk/10.3390/math10040534 - 09 Feb 2022
Cited by 9 | Viewed by 2139
Abstract
In interval analysis, the fuzzy inclusion relation and the fuzzy order relation are two different concepts. Under the inclusion connection, convexity and non-convexity form a substantial link with various types of inequalities. Moreover, convex fuzzy-interval-valued functions are well known in convex theory because [...] Read more.
In interval analysis, the fuzzy inclusion relation and the fuzzy order relation are two different concepts. Under the inclusion connection, convexity and non-convexity form a substantial link with various types of inequalities. Moreover, convex fuzzy-interval-valued functions are well known in convex theory because they allow us to infer more exact inequalities than convex functions. Most likely, integral operators play significant roles to define different types of inequalities. In this paper, we have successfully introduced the Riemann–Liouville fractional integrals on coordinates via fuzzy-interval-valued functions (FIVFs). Then, with the help of these integrals, some fuzzy fractional Hermite–Hadamard-type integral inequalities are also derived for the introduced coordinated convex FIVFs via a fuzzy order relation (FOR). This FOR is defined by φ-cuts or level-wise by using the Kulish–Miranker order relation. Moreover, some related fuzzy fractional Hermite–Hadamard-type integral inequalities are also obtained for the product of two coordinated convex fuzzy-interval-valued functions. The main results of this paper are the generalization of several known results. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
16 pages, 306 KiB  
Article
A Study of Spaces of Sequences in Fuzzy Normed Spaces
by Ju-Myung Kim and Keun-Young Lee
Mathematics 2021, 9(9), 1040; https://0-doi-org.brum.beds.ac.uk/10.3390/math9091040 - 04 May 2021
Cited by 1 | Viewed by 1626
Abstract
In this paper, spaces of sequences in fuzzy normed spaces are considered. These spaces are a new concept in fuzzy normed spaces. We develop fuzzy norms for spaces of sequences in fuzzy normed spaces. Especially, we study the representation of the dual of [...] Read more.
In this paper, spaces of sequences in fuzzy normed spaces are considered. These spaces are a new concept in fuzzy normed spaces. We develop fuzzy norms for spaces of sequences in fuzzy normed spaces. Especially, we study the representation of the dual of a space of sequences in a fuzzy normed space. The approximation property in our context is investigated. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
17 pages, 805 KiB  
Article
Graph Convolutional Network for Drug Response Prediction Using Gene Expression Data
by Seonghun Kim, Seockhun Bae, Yinhua Piao and Kyuri Jo
Mathematics 2021, 9(7), 772; https://0-doi-org.brum.beds.ac.uk/10.3390/math9070772 - 02 Apr 2021
Cited by 18 | Viewed by 7372
Abstract
Genomic profiles of cancer patients such as gene expression have become a major source to predict responses to drugs in the era of personalized medicine. As large-scale drug screening data with cancer cell lines are available, a number of computational methods have been [...] Read more.
Genomic profiles of cancer patients such as gene expression have become a major source to predict responses to drugs in the era of personalized medicine. As large-scale drug screening data with cancer cell lines are available, a number of computational methods have been developed for drug response prediction. However, few methods incorporate both gene expression data and the biological network, which can harbor essential information about the underlying process of the drug response. We proposed an analysis framework called DrugGCN for prediction of Drug response using a Graph Convolutional Network (GCN). DrugGCN first generates a gene graph by combining a Protein-Protein Interaction (PPI) network and gene expression data with feature selection of drug-related genes, and the GCN model detects the local features such as subnetworks of genes that contribute to the drug response by localized filtering. We demonstrated the effectiveness of DrugGCN using biological data showing its high prediction accuracy among the competing methods. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

26 pages, 364 KiB  
Article
On Unification of Methods in Theories of Fuzzy Sets, Hesitant Fuzzy Set, Fuzzy Soft Sets and Intuitionistic Fuzzy Sets
by Jiří Močkoř and David Hýnar
Mathematics 2021, 9(4), 447; https://0-doi-org.brum.beds.ac.uk/10.3390/math9040447 - 23 Feb 2021
Cited by 12 | Viewed by 1764
Abstract
The main goal of this publication is to show that the basic constructions in the theories of fuzzy sets, fuzzy soft sets, fuzzy hesitant sets or intuitionistic fuzzy sets have a common background, based on the theory of monads in categories. It is [...] Read more.
The main goal of this publication is to show that the basic constructions in the theories of fuzzy sets, fuzzy soft sets, fuzzy hesitant sets or intuitionistic fuzzy sets have a common background, based on the theory of monads in categories. It is proven that ad hoc defined basic concepts in individual theories, such as concepts of power set structures in these theories, relations or approximation operators defined by these relations are only special examples of applications of the monad theory in categories. This makes it possible, on the one hand, to unify basic constructions in all these theories and, on the other hand, to verify the legitimacy of ad hoc definitions of these constructions in individual theories. This common background also makes it possible to transform these basic concepts from one theory to another. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
14 pages, 862 KiB  
Article
Several Limit Theorems on Fuzzy Quantum Space
by Viliam Ďuriš, Renáta Bartková and Anna Tirpáková
Mathematics 2021, 9(4), 438; https://0-doi-org.brum.beds.ac.uk/10.3390/math9040438 - 23 Feb 2021
Cited by 1 | Viewed by 1712
Abstract
The probability theory using fuzzy random variables has applications in several scientific disciplines. These are mainly technical in scope, such as in the automotive industry and in consumer electronics, for example, in washing machines, televisions, and microwaves. The theory is gradually entering the [...] Read more.
The probability theory using fuzzy random variables has applications in several scientific disciplines. These are mainly technical in scope, such as in the automotive industry and in consumer electronics, for example, in washing machines, televisions, and microwaves. The theory is gradually entering the domain of finance where people work with incomplete data. We often find that events in the financial markets cannot be described precisely, and this is where we can use fuzzy random variables. By proving the validity of the theorem on extreme values of fuzzy quantum space in our article, we see possible applications for estimating financial risks with incomplete data. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

20 pages, 506 KiB  
Article
Path-Planning for Mobile Robots Using a Novel Variable-Length Differential Evolution Variant
by Alejandro Rodríguez-Molina, José Solís-Romero, Miguel Gabriel Villarreal-Cervantes, Omar Serrano-Pérez and Geovanni Flores-Caballero
Mathematics 2021, 9(4), 357; https://0-doi-org.brum.beds.ac.uk/10.3390/math9040357 - 11 Feb 2021
Cited by 8 | Viewed by 1973
Abstract
Mobile robots are currently exploited in various applications to enhance efficiency and reduce risks in hard activities for humans. The high autonomy in those systems is strongly related to the path-planning task. The path-planning problem is complex and requires in its formulation the [...] Read more.
Mobile robots are currently exploited in various applications to enhance efficiency and reduce risks in hard activities for humans. The high autonomy in those systems is strongly related to the path-planning task. The path-planning problem is complex and requires in its formulation the adjustment of path elements that take the mobile robot from a start point to a target one at the lowest cost. Nevertheless, the identity or the number of the path elements to be adjusted is unknown; therefore, the human decision is necessary to determine this information reducing autonomy. Due to the above, this work conceives the path-planning as a Variable-Length-Vector optimization problem (VLV-OP) where both the number of variables (path elements) and their values must be determined. For this, a novel variant of Differential Evolution for Variable-Length-Vector optimization named VLV-DE is proposed to handle the path-planning VLV-OP for mobile robots. VLV-DE uses a population with solution vectors of different sizes adapted through a normalization procedure to allow interactions and determine the alternatives that better fit the problem. The effectiveness of this proposal is shown through the solution of the path-planning problem in complex scenarios. The results are contrasted with the well-known A* and the RRT*-Smart path-planning methods. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

18 pages, 1935 KiB  
Article
New Product Idea Selection in the Fuzzy Front End of Innovation: A Fuzzy Best-Worst Method and Group Decision-Making Process
by Shui Ming Li, Felix T. S. Chan, Yung Po Tsang and Hoi Yan Lam
Mathematics 2021, 9(4), 337; https://0-doi-org.brum.beds.ac.uk/10.3390/math9040337 - 08 Feb 2021
Cited by 11 | Viewed by 3044
Abstract
New product development (NPD) is essential to most business organizations to create new values and protect existing values for maintaining high profitability and sustainability. However, the success of NPD projects is deemed to be difficult and challenging owing to high organizational complexity, uncertain [...] Read more.
New product development (NPD) is essential to most business organizations to create new values and protect existing values for maintaining high profitability and sustainability. However, the success of NPD projects is deemed to be difficult and challenging owing to high organizational complexity, uncertain business environment, and time-critical innovation. Under the smart manufacturing paradigm, NPD is an active research area to establish effective measures through the adoption of systematic approaches so as to facilitate idea management in the fuzzy front end for the product innovation. In this paper, the domain of new product idea selection is focused on and enhanced by means of the multi-criteria decision-making (MCDM) approach, in which multiple criteria and sub-criteria can be considered in the selection process. Among a number of MCDM approaches, the fuzzy set theory and best-worst method (BWM) are integrated as the fuzzy BWM in this study to structure the new product idea selection process under a group decision-making process. The hierarchy structure for the new product idea selection is also established to consider the perspectives of finance, marketing, engineering, manufacturing, and sustainability. Overall speaking, this study contributes to the field of NPD through overcoming the new product idea selection problem, while the group decision-making process is incorporated into the fuzzy BWM. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

15 pages, 4062 KiB  
Article
An Intuitionistic Fuzzy Set Driven Stochastic Active Contour Model with Uncertainty Analysis
by Bin Wang, Yaoqing Li and Jianlong Zhang
Mathematics 2021, 9(4), 301; https://0-doi-org.brum.beds.ac.uk/10.3390/math9040301 - 03 Feb 2021
Cited by 2 | Viewed by 1460
Abstract
Image segmentation is a process that densely classifies image pixels into different regions corresponding to real world objects. However, this correspondence is not always exact in images since there are many uncertainty factors, e.g., recognition hesitation, imaging equipment, condition, and atmosphere environment. To [...] Read more.
Image segmentation is a process that densely classifies image pixels into different regions corresponding to real world objects. However, this correspondence is not always exact in images since there are many uncertainty factors, e.g., recognition hesitation, imaging equipment, condition, and atmosphere environment. To achieve the segmentation result with low uncertainty and reduce the influence on the subsequent procedures, e.g., image parsing and image understanding, we propose a novel stochastic active contour model based on intuitionistic fuzzy set, in which the hesitation degree is leveraged to model the recognition uncertainty in image segmentation. The advantages of our model are as follows. (1) Supported by fuzzy partition, our model is robust against image noise and inhomogeneity. (2) Benefiting from the stochastic process, our model easily crosses saddle points of energy functional. (3) Our model realizes image segmentation with low uncertainty and co-produces the quantitative uncertainty degree to the segmentation results, which is helpful to improve reliability of intelligent image systems. The associated experiments suggested that our model could obtain competitive segmentation results compared to the relevant state-of-the-art active contour models and could provide segmentation with a pixel-wise uncertainty degree. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

35 pages, 543 KiB  
Article
Induced OWA Operator for Group Decision Making Dealing with Extended Comparative Linguistic Expressions with Symbolic Translation
by Wen He, Bapi Dutta, Rosa M. Rodríguez, Ahmad A. Alzahrani and Luis Martínez
Mathematics 2021, 9(1), 20; https://0-doi-org.brum.beds.ac.uk/10.3390/math9010020 - 23 Dec 2020
Cited by 12 | Viewed by 1776
Abstract
Nowadays, decision making problems have increased their complexity and a single decision maker cannot handle these problems, with a more diverse and comprehensive view of them being necessary, which results in group decision making (GDM) schemes. The complexity of GDM problems is often [...] Read more.
Nowadays, decision making problems have increased their complexity and a single decision maker cannot handle these problems, with a more diverse and comprehensive view of them being necessary, which results in group decision making (GDM) schemes. The complexity of GDM problems is often due to their inherent uncertainty that is not solved just by using a group. Consequently, different methodologies has been proposed to handle it, in which, the use of the fuzzy linguistic approach stands out. Among the multiple fuzzy linguistic modeling approaches, Extended Comparative Linguistic Expressions with Symbolic Translation (ELICIT) information has been recently introduced, which enhances classical linguistic modeling that is based on single terms by providing linguistic expressions in a continuous linguistic domain. Its application to decision making is quite promising, but it is necessary to develop enough operators to accomplish aggregation processes in the decision solving scheme. So far, just a small number of aggregation operators have been defined for ELICIT information. Hence, this paper aims at providing new aggregation operators for ELICIT information by developing novel OWA based operators, such as the Induced OWA (IOWA) operator in order to avoid the OWA operator needs of reordering its arguments, because ELICIT information does not have an inherent order due to its fuzzy representation. Our proposal not only consists of extending the definition of an IOWA operator for ELICIT information with crisp weights, but it is also proposed a type-1 IOWA operator for ELICIT information in which both weights and arguments are fuzzy as well as the use of ELICIT information constructing the order inducing variable to reorder the arguments. Additionally, the use of ELICIT information in GDM demands the ability to manage majority based decisions that are better represented in the IOWA operator by linguistic quantifiers. Hence, a majority-driven GDM process for ELICIT information is proposed, which it is the first proposal for fulfilling the majority solving process for GDM while using ELICIT information. Eventually, an illustrative example and a brief comparative analysis are presented in order to show the performance of the proposal and its feasibility. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

22 pages, 2617 KiB  
Article
A Consensus Model for Extended Comparative Linguistic Expressions with Symbolic Translation
by Álvaro Labella, Rosa M. Rodríguez, Ahmad A. Alzahrani and Luis Martínez
Mathematics 2020, 8(12), 2198; https://0-doi-org.brum.beds.ac.uk/10.3390/math8122198 - 10 Dec 2020
Cited by 7 | Viewed by 1766
Abstract
Consensus Reaching Process (CRP) is a necessary process to achieve agreed solutions in group decision making (GDM) problems. Usually, these problems are defined in uncertain contexts, in which experts do not have a full and precise knowledge about all aspects of the problem. [...] Read more.
Consensus Reaching Process (CRP) is a necessary process to achieve agreed solutions in group decision making (GDM) problems. Usually, these problems are defined in uncertain contexts, in which experts do not have a full and precise knowledge about all aspects of the problem. In real-world GDM problems under uncertainty, it is usual that experts express their preferences by using linguistic expressions. Consequently, different methodologies have modelled linguistic information, in which computing with words stands out and whose basis is the fuzzy linguistic approach and their extensions. Even though, multiple consensus approaches under fuzzy linguistic environments have been proposed in the specialized literature, there are still some areas where their performance must be improved because of several persistent drawbacks. The drawbacks include the use of single linguistic terms that are not always enough to model the uncertainty in experts’ knowledge or the oversimplification of fuzzy information during the computational processes by defuzzification processes into crisp values, which usually implies a loss of information and precision in the results and also a lack of interpretability. Therefore, to improving the effects of previous drawbacks, this paper aims at presenting a novel CRP for GDM problems dealing with Extended Comparative Linguistic Expressions with Symbolic Translation (ELICIT) for modelling experts’ linguistic preferences. Such a CRP will overcome previous limitations because ELICIT information allows both fuzzy modelling of the experts’ uncertainty including hesitancy and performs comprehensive fuzzy computations to, ultimately, obtain precise and understandable linguistic results. Additionally, the proposed CRP model is implemented and integrated into the CRP support system so-called A FRamework for the analYsis of Consensus Approaches (AFRYCA) 3.0 that facilitates the application of the proposed CRP and its comparison with previous models. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

26 pages, 583 KiB  
Article
Barrakuda: A Hybrid Evolutionary Algorithm for Minimum Capacitated Dominating Set Problem
by Pedro Pinacho-Davidson and Christian Blum
Mathematics 2020, 8(11), 1858; https://0-doi-org.brum.beds.ac.uk/10.3390/math8111858 - 23 Oct 2020
Cited by 4 | Viewed by 2152
Abstract
The minimum capacitated dominating set problem is an NP-hard variant of the well-known minimum dominating set problem in undirected graphs. This problem finds applications in the context of clustering and routing in wireless networks. Two algorithms are presented in this work. The first [...] Read more.
The minimum capacitated dominating set problem is an NP-hard variant of the well-known minimum dominating set problem in undirected graphs. This problem finds applications in the context of clustering and routing in wireless networks. Two algorithms are presented in this work. The first one is an extended version of construct, merge, solve and adapt, while the main contribution is a hybrid between a biased random key genetic algorithm and an exact approach which we labeled Barrakuda. Both algorithms are evaluated on a large set of benchmark instances from the literature. In addition, they are tested on a new, more challenging benchmark set of larger problem instances. In the context of the problem instances from the literature, the performance of our algorithms is very similar. Moreover, both algorithms clearly outperform the best approach from the literature. In contrast, Barrakuda is clearly the best-performing algorithm for the new, more challenging problem instances. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

16 pages, 1171 KiB  
Article
An Integrated Decision Approach with Probabilistic Linguistic Information for Test Case Prioritization
by A. D. Shrivathsan, R. Krishankumar, Arunodaya Raj Mishra, K. S. Ravichandran, Samarjit Kar and V. Badrinath
Mathematics 2020, 8(11), 1857; https://0-doi-org.brum.beds.ac.uk/10.3390/math8111857 - 23 Oct 2020
Cited by 6 | Viewed by 1844
Abstract
This paper focuses on an exciting and essential problem in software companies. The software life cycle includes testing software, which is often time-consuming, and is a critical phase in the software development process. To reduce time spent on testing and to maintain software [...] Read more.
This paper focuses on an exciting and essential problem in software companies. The software life cycle includes testing software, which is often time-consuming, and is a critical phase in the software development process. To reduce time spent on testing and to maintain software quality, the idea of a systematic selection of test cases is needed. Attracted by the claim, researchers presented test case prioritization (TCP) by applying the concepts of multi-criteria decision-making (MCDM). However, the literature on TCP suffers from the following issues: (i) difficulty in properly handling uncertainty; (ii) systematic evaluation of criteria by understanding the hesitation of experts; and (iii) rational prioritization of test cases by considering the nature of criteria. Motivated by these issues, an integrated approach is put forward that could circumvent the problem in this paper. The main aim of this research is to develop a decision model with integrated methods for TCP. The core importance of the proposed model is to (i) provide a systematic/methodical decision on TCP with a reduction in testing time and cost; (ii) help software personnel choose an apt test case from the suite for testing software; (iii) reduce human bias by mitigating intervention of personnel in the decision process. To this end, probabilistic linguistic information (PLI) is adopted as the preference structure that could flexibly handle uncertainty by associating occurrence probability to each linguistic term. Furthermore, an attitude-based entropy measure is presented for criteria weight calculation, and finally, the EDAS ranking method is extended to PLI for TCP. An empirical study of TCP in a software company is presented to certify the integrated approach’s effectiveness. The strengths and weaknesses of the introduced approach are conferred by comparing it with the relevant methods. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

22 pages, 2611 KiB  
Article
Comparing Built-in Power Banks for a Smart Backpack Design Using an Auto-Weighting Fuzzy-Weighted-Intersection FAHP Approach
by Hsin-Chieh Wu, Tin-Chih Toly Chen, Chin-Hau Huang and Yun-Cian Shih
Mathematics 2020, 8(10), 1759; https://0-doi-org.brum.beds.ac.uk/10.3390/math8101759 - 13 Oct 2020
Cited by 12 | Viewed by 1977
Abstract
Smart backpacks are a prevalent application of smart technologies, with functions such as motion recording, navigation, and energy harvesting and provision. Selecting a suitable built-in power bank is a critical task for a smart backpack design, which has rarely been investigated in the [...] Read more.
Smart backpacks are a prevalent application of smart technologies, with functions such as motion recording, navigation, and energy harvesting and provision. Selecting a suitable built-in power bank is a critical task for a smart backpack design, which has rarely been investigated in the past. To fulfill this task, an auto-weighting fuzzy-weighted-intersection fuzzy analytic hierarchy process (FAHP) approach is proposed in this study. When decision makers lack an overall consensus, the auto-weighting fuzzy-weighted-intersection FAHP approach specifies decision makers’ authority levels according to the consistency ratios of their judgments. In this way, the consensus among all decision makers can be sought. The auto-weighting fuzzy-weighted-intersection FAHP approach has been applied to compare six mobile power banks for a smart backpack design. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

28 pages, 2036 KiB  
Article
An Improved Migrating Birds Optimization Algorithm for a Hybrid Flow Shop Scheduling within Steel Plants
by Dayong Han, Qiuhua Tang, Zikai Zhang and Zixiang Li
Mathematics 2020, 8(10), 1661; https://0-doi-org.brum.beds.ac.uk/10.3390/math8101661 - 26 Sep 2020
Cited by 12 | Viewed by 2064
Abstract
Steelmaking and the continuous-casting (SCC) scheduling problem is a realistic hybrid flow shop scheduling problem with continuous-casting production at the last stage. This study considers the SCC scheduling problem with diverse products, which is a vital and difficult problem in steel plants. To [...] Read more.
Steelmaking and the continuous-casting (SCC) scheduling problem is a realistic hybrid flow shop scheduling problem with continuous-casting production at the last stage. This study considers the SCC scheduling problem with diverse products, which is a vital and difficult problem in steel plants. To tackle this problem, this study first presents the mixed-integer linear programming (MILP) model to minimize the objective of makespan. Then, an improved migrating birds optimization algorithm (IMBO) is proposed to tackle this considered NP-hard problem. In the proposed IMBO, several improvements are employed to achieve the proper balance between exploration and exploitation. Specifically, a two-level decoding procedure is designed to achieve feasible solutions; the simulated annealing-based acceptance criterion is employed to ensure the diversity of the population and help the algorithm to escape from being trapped in local optima; a competitive mechanism is developed to emphasize exploitation capacity by searching around the most promising solution space. The computational experiments demonstrate that the proposed IMBO obtains competing performance and it outperforms seven other implemented algorithms in the comparative study. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

42 pages, 460 KiB  
Article
Arithmetics of Vectors of Fuzzy Sets
by Hsien-Chung Wu
Mathematics 2020, 8(9), 1614; https://0-doi-org.brum.beds.ac.uk/10.3390/math8091614 - 18 Sep 2020
Cited by 1 | Viewed by 1722
Abstract
The arithmetic operations of fuzzy sets are completely different from the arithmetic operations of vectors of fuzzy sets. In this paper, the arithmetic operations of vectors of fuzzy intervals are studied by using the extension principle and a form of decomposition theorem. These [...] Read more.
The arithmetic operations of fuzzy sets are completely different from the arithmetic operations of vectors of fuzzy sets. In this paper, the arithmetic operations of vectors of fuzzy intervals are studied by using the extension principle and a form of decomposition theorem. These two different methodologies lead to the different types of membership functions. We establish their equivalences under some mild conditions. On the other hand, the α-level sets of addition, difference and scalar products of vectors of fuzzy intervals are also studied, which will be useful for the different usage in applications. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
30 pages, 574 KiB  
Article
Minkowski Weighted Score Functions of Intuitionistic Fuzzy Values
by Feng Feng, Yujuan Zheng, José Carlos R. Alcantud and Qian Wang
Mathematics 2020, 8(7), 1143; https://0-doi-org.brum.beds.ac.uk/10.3390/math8071143 - 13 Jul 2020
Cited by 25 | Viewed by 2583
Abstract
In multiple attribute decision-making in an intuitionistic fuzzy environment, the decision information is sometimes given by intuitionistic fuzzy soft sets. In order to address intuitionistic fuzzy decision-making problems in a more efficient way, many scholars have produced increasingly better procedures for ranking intuitionistic [...] Read more.
In multiple attribute decision-making in an intuitionistic fuzzy environment, the decision information is sometimes given by intuitionistic fuzzy soft sets. In order to address intuitionistic fuzzy decision-making problems in a more efficient way, many scholars have produced increasingly better procedures for ranking intuitionistic fuzzy values. In this study, we further investigate the problem of ranking intuitionistic fuzzy values from a geometric point of view, and we produce related applications to decision-making. We present Minkowski score functions of intuitionistic fuzzy values, which are natural generalizations of the expectation score function and other useful score functions in the literature. The rationale for Minkowski score functions lies in the geometric intuition that a better score should be assigned to an intuitionistic fuzzy value farther from the negative ideal intuitionistic fuzzy value. To capture the subjective attitude of decision makers, we further propose the Minkowski weighted score function that incorporates an attitudinal parameter. The Minkowski score function is a special case corresponding to a neutral attitude. Some fundamental properties of Minkowski (weighted) score functions are examined in detail. With the aid of the Minkowski weighted score function and the maximizing deviation method, we design a new algorithm for solving decision-making problems based on intuitionistic fuzzy soft sets. Moreover, two numerical examples regarding risk investment and supplier selection are employed to conduct comparative analyses and to demonstrate the feasibility of the approach proposed in this article. Full article
(This article belongs to the Special Issue Fuzzy Sets and Soft Computing)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-16
Back to TopTop