Applications of Fuzzy Optimization

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 March 2022) | Viewed by 33542

Special Issue Editor

Department of Computer Science, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa, Poland
Interests: development of modeling; identification; decision-making and optimization methods under conditions of objective (stochastic) and non-probabilistic (interval, fuzzy, possibilistic, etc.) types of uncertainty in economic, technological and ecological applications

Special Issue Information

Dear Colleagues,

In general, “fuzzy optimization” comprises a lot of problems, which can be roughly divided into two clasters: the problems of task formulation under different types  of uncertainty and the problems  of solution methods development. In my opinion, the first group of problems seems to be more important, since even an excellent solution of incorrectly formulated problems usually does not make sense. Therefore, papers devoted to methodological problems of local criteria formalization, their  aggregation, as well as the generalization of aggregation methods under a wide spectrum of uncertainties, such as interval, fuzzy, type 2 fuzzy, interval-valued fuzzy, intuitionistic fuzzy, hesitant fuzzy, evidential (Dempster–Shafer theory of evidence), etc., and their different combinations will be encouraged in this Special Issue in the first place. On the other hand, to fulfill the criterion of truth, the theoretical presentations should be accompanied by convincing, desirable real-word examples, and by the results of real problems solutions in different branches of technology, medicine, ecology, finance, etc. Of course, we welcome researchers who are focused on the development of new methods for the solution of optimization tasks under different types of uncertainty, with their real-world applications. Methods which are not entirely based on the direct reduction of a fuzzy problem to a real-valued one are particularly encouraged. Review papers presenting the modern state of the art in the promising directions in the field of fuzzy optimizations would also be interesting for researchers.

Prof. Ludmila Dymova
Guest Editor

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Keywords

  • Local criteria mathematical formalization under uncertainty
  • Local criteria aggregation and aggregation of aggregating modes
  • Interval type of uncertainty
  • Fuzzy type of uncertainty
  • Type 2 fuzzy sets
  • Interval-valued fuzzy sets
  • Intuitionistic fuzzy sets
  • Hesitant fuzzy sets
  • Dempster–Shafer theory of evidence
  • Methods for the solution of fuzzy optimization problems

Published Papers (17 papers)

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Research

18 pages, 358 KiB  
Article
Comparing a Fuzzy Hybrid Approach with Invariant MGCFA to Study National Identity
by Juan Carlos Martín and Alessandro Indelicato
Appl. Sci. 2023, 13(3), 1657; https://0-doi-org.brum.beds.ac.uk/10.3390/app13031657 - 28 Jan 2023
Cited by 5 | Viewed by 1107
Abstract
National identity studies diverge on several issues, such as the number of factors and their respective items’ adscription. Multi-Group Confirmatory Factor Analysis (MGCFA) is the standard method applied to cross-national datasets. Differences between groups can be the result of measurement artefacts. We argue [...] Read more.
National identity studies diverge on several issues, such as the number of factors and their respective items’ adscription. Multi-Group Confirmatory Factor Analysis (MGCFA) is the standard method applied to cross-national datasets. Differences between groups can be the result of measurement artefacts. We argue that these problems can be better addressed by an alternative approach that builds a synthetic indicator named Relative National Identity Synthetic Indicator (RNISI), based on a Fuzzy Hybrid Analysis (FHA). The study aims to shed some light on the study of the latent variable national identity by comparing two methodologies: the classic method most often used (MGCFA) and the Fuzzy-Hybrid Approach, which, to our knowledge, has not been previously applied. This empirical study was based on a dataset from across ten countries using two waves (2003 and 2013) of the International Social Survey Programme (ISSP). The FHA results were compared with those obtained by two MGCFA models in which national identity was built as a second-order construct that depends on the ethnic, ancestry and civic first-order latent variables. The comparison lets us conclude that FHA can be considered a valid tool to measure the national identity by groups, and to provide additional information in form of elasticity figures. These figures can be employed to analyse the indicator’s sensitivity by group and for each of the items included in the national identity construct. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
13 pages, 27082 KiB  
Communication
Straight-Line Path Tracking Control of Agricultural Tractor-Trailer Based on Fuzzy Sliding Mode Control
by Wenyue Huang, Xin Ji, Anzhe Wang, Yefei Wang and Xinhua Wei
Appl. Sci. 2023, 13(2), 872; https://0-doi-org.brum.beds.ac.uk/10.3390/app13020872 - 08 Jan 2023
Cited by 3 | Viewed by 1227
Abstract
In order to solve the labor shortage problem, unmanned agricultural vehicles have been widely promoted in China. Among these vehicles, unmanned tractor-trailers have garnered the most interest thanks to their flexibility and efficiency. However, trapped by the factors of vehicle parameter uncertainties, unstructured [...] Read more.
In order to solve the labor shortage problem, unmanned agricultural vehicles have been widely promoted in China. Among these vehicles, unmanned tractor-trailers have garnered the most interest thanks to their flexibility and efficiency. However, trapped by the factors of vehicle parameter uncertainties, unstructured farmland roads, etc., the current unmanned tractor-trailers have shown poor tracking accuracy and longer online times in straight-line path tracking. To overcome the aforementioned issues, a fuzzy sliding mode control (FSMC) approach is proposed in this paper. First, the tractor-trailer path tracking error model was established based on the kinematic model and a reference model. Then, according to the sliding mode control (SMC) theory, the FSMC was designed. Through a Lyapunov theory analysis, the proposed control method can ensure that the articulated angle, the position error, and the heading error all converge to zero. Finally, field tests and Simulink simulations demonstrated the effectiveness and robustness of the suggested control mechanism. According to field experiments, the proposed control method can increase the trailer steady-state tracking accuracy by between 10.5 and 36.8% and the tractor steady-state tracking accuracy by between 11.1 and 50%. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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22 pages, 617 KiB  
Article
Realistic Optimal Tolerant Solution of the Quadratic Interval Equation and Determining the Optimal Control Decision on the Example of Plant Fertilization
by Andrzej Piegat and Marcin Pluciński
Appl. Sci. 2022, 12(21), 10725; https://0-doi-org.brum.beds.ac.uk/10.3390/app122110725 - 23 Oct 2022
Cited by 2 | Viewed by 910
Abstract
In scientific journals, it is increasingly common to find articles presenting methods for solving problems not based on idealistic mathematical models containing perfectly accurate coefficient values that cannot be obtained in practice, but on models in which coefficient values are affected by uncertainty [...] Read more.
In scientific journals, it is increasingly common to find articles presenting methods for solving problems not based on idealistic mathematical models containing perfectly accurate coefficient values that cannot be obtained in practice, but on models in which coefficient values are affected by uncertainty and are expressed in the form of intervals, fuzzy numbers, etc. However, solving tasks with interval coefficients is not fully mastered, and a number of such problems cannot be solved by currently known methods. There is undeniably a research gap here. The article presents a method for solving problems governed by the quadratic interval equation and shows how to find the tolerant optimal control value of such a system. This makes it possible to solve problems that could not be solved before. The paper introduces a new concept of the degree of robustness of the control to the set of all possible multidimensional states of the system resulting from its uncertainties. The method presented in the article was applied to an example of determining the optimal value of nitrogen fertilization of a sugar beet plantation, the vegetation of which is under uncertainty. It would be unrealistic to assume precise knowledge of crop characteristics here. The proposed method allows to determine the value of fertilization, which gives a chance to obtain the desired yield for the maximum number of field conditions that can occur during the growing season. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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21 pages, 794 KiB  
Article
The Optimal Tolerance Solution of the Basic Interval Linear Equation and the Explanation of the Lodwick’s Anomaly
by Andrzej Piegat and Marcin Pluciński
Appl. Sci. 2022, 12(9), 4382; https://0-doi-org.brum.beds.ac.uk/10.3390/app12094382 - 26 Apr 2022
Cited by 4 | Viewed by 1530
Abstract
Determining the tolerance solution (TS) of interval linear systems (ILSs) has been a task under consideration for many years. It seems, however, that this task has not been fully and unequivocally solved. This is evidenced by the multiplicity of proposed methods (which sometimes [...] Read more.
Determining the tolerance solution (TS) of interval linear systems (ILSs) has been a task under consideration for many years. It seems, however, that this task has not been fully and unequivocally solved. This is evidenced by the multiplicity of proposed methods (which sometimes provide different results), the existence of many questions, and the emergence of strange solutions provided by, for example, Lodwick’s interval equation anomaly (LIEA). The problem of solving ILEs is probably more difficult than we think. The article presents a new method of ILSs solving, but it is limited to the simplest, basic equation [a̲,a¯]X=[b̲,b¯], which is an element of all more complex forms of ILSs. The method finds the optimal TS for this equation by using multidimensional interval arithmetic (MIA). According to the authors’ knowledge, this is a new method and it will allow researchers to solve more complex forms of ILSs and various types of nonlinear interval equations. It can also be used to solve fuzzy linear systems (FLSs). The paper presents several examples of the method applications (including one real-life case). Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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20 pages, 2059 KiB  
Article
Two Approaches to Analyze Whether Citizens’ National Identity Is Affected by Country, Age, and Political Orientation—A Fuzzy Eco-Apostle Model
by Alessandro Indelicato and Juan Carlos Martín
Appl. Sci. 2022, 12(8), 3946; https://0-doi-org.brum.beds.ac.uk/10.3390/app12083946 - 13 Apr 2022
Cited by 7 | Viewed by 2218
Abstract
The study analyzes national identity using the International Social Survey Program (ISSP) database for the waves of 2003 and 2013. First, the Exploratory Factor Analysis (EFA) and the Multigroup Confirmatory Factor Analysis (MGCFA) are used to find the dimensions of the items included [...] Read more.
The study analyzes national identity using the International Social Survey Program (ISSP) database for the waves of 2003 and 2013. First, the Exploratory Factor Analysis (EFA) and the Multigroup Confirmatory Factor Analysis (MGCFA) are used to find the dimensions of the items included in the national identity module. Second, the civic and ethnic dimensions are analyzed through both a fuzzy clustering analysis and an extended apostle model to classify citizens’ national identity as the following: (1) post nationalists; (2) ethnic oriented; (3) civic-oriented; (4) credentialists. Third, the fuzzy eco-extended apostle model is applied to analyze 16 different national identity categories, for which the four pure mentioned categories are further studied. Fourth, the effects of some social characteristics, such as country-year, political orientation-year, and age-year, on the respective pure national Identity categories are studied using two distinct approaches, namely, contingency tables and conditional probability ratios. Results show that citizens tend to be more pure-credentialist than any other category and that social characteristics play a determinant role in explaining each category of citizens’ national identity. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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25 pages, 1277 KiB  
Article
Design and Optimization of a Neuro-Fuzzy System for the Control of an Electromechanical Plant
by Helbert Espitia, Iván Machón and Hilario López
Appl. Sci. 2022, 12(2), 541; https://0-doi-org.brum.beds.ac.uk/10.3390/app12020541 - 06 Jan 2022
Cited by 2 | Viewed by 1514
Abstract
One characteristic of neuro-fuzzy systems is the possibility of incorporating preliminary information in their structure as well as being able to establish an initial configuration to carry out the training. In this regard, the strategy to establish the configuration of the fuzzy system [...] Read more.
One characteristic of neuro-fuzzy systems is the possibility of incorporating preliminary information in their structure as well as being able to establish an initial configuration to carry out the training. In this regard, the strategy to establish the configuration of the fuzzy system is a relevant aspect. This document displays the design and implementation of a neuro-fuzzy controller based on Boolean relations to regulate the angular position in an electromechanical plant, composed by a motor coupled to inertia with friction (a widely studied plant that serves to show the control system design process). The structure of fuzzy systems based on Boolean relations considers the operation of sensors and actuators present in the control system. In this way, the initial configuration of fuzzy controller can be determined. In order to perform the optimization of the neuro-fuzzy controller, the continuous plant model is converted to discrete time to be included in the closed-loop controller training equations. For the design process, first the optimization of a Proportional Integral (PI) linear controller is carried out. Thus, linear controller parameters are employed to establish the structure and initial configuration of the neuro-fuzzy controller. The optimization process also includes weighting factors for error and control action in such a way that allows having different system responses. Considering the structure of the control system, the optimization algorithm (training algorithm) employed is dynamic back propagation. The results via simulations show that optimization is achieved in the linear and neuro-fuzzy controllers using different weighting values for the error signal and control action. It is also observed that the proposed control strategy allows disturbance rejection. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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15 pages, 1120 KiB  
Article
A Hybrid MCDM Model for Live-Streamer Selection via the Fuzzy Delphi Method, AHP, and TOPSIS
by You Rang Lim, Aini Suzana Ariffin, Mazlan Ali and Kuei-Lun Chang
Appl. Sci. 2021, 11(19), 9322; https://0-doi-org.brum.beds.ac.uk/10.3390/app11199322 - 08 Oct 2021
Cited by 10 | Viewed by 2736
Abstract
The development of the Internet is a key revolution of the 20th century. The Internet has led to a boom in e-commerce. Online shopping is generally the most popular shopping option for consumers. The coronavirus disease 2019 (COVID-19) pandemic has resulted in adopting [...] Read more.
The development of the Internet is a key revolution of the 20th century. The Internet has led to a boom in e-commerce. Online shopping is generally the most popular shopping option for consumers. The coronavirus disease 2019 (COVID-19) pandemic has resulted in adopting various measures, such as lockdown and stay-at-home orders, in various countries. This has led to changes in people’s consumption habits. In Taiwan, consumer behavior has also rapidly shifted to online shopping after the outbreak of the COVID-19. As livestreaming breaks time and space barriers, its real-time, interactive, and authentic features are unparalleled compared to other marketing methods, thereby creating a brand-new shopping experience for consumers. Accordingly, livestream shopping, a new consumption model, has developed and become an essential part of people’s daily lives. Live-streamers, who are similar to salespersons in traditional markets, play a vital role in e-commerce livestreaming. The success of livestream shopping has highlighted the importance of live-streamers. The competition among live-streamers has become more intense because of the arrival of many newcomers. Thus, operators must make careful hiring decisions. However, no related literature in the past has investigated this important topic. Therefore, this study applied a hybrid multi-criteria decision-making (MCDM) model comprising the fuzzy Delphi method (screen the selection criteria), analytic hierarchy process (AHP) (obtain the weight of each dimension and criterion), and technique for order preference by similarity to ideal solution (TOPSIS) (rank the alternatives) to assist the managers of shopping websites in selecting live-streamers. We interviewed the managers of shopping websites and reviewed the related literature to compile the selection criteria. Following the fuzzy Delphi method, 15 important selection criteria were retained based on the 30 managers’ opinions. Further, the criteria were classified into dimensions based on the previous literature and interviews conducted on managers to establish a hierarchical framework. On the basis of this hierarchical framework, AHP and TOPSIS were applied to help a case company select live-streamers. A comparative analysis between the outcomes from AHP and AHP/TOPSIS was also conducted in this study. This study is the first empirical study on live-streamers’ selection and adds to the literature on livestreaming. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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22 pages, 878 KiB  
Article
Fuzzy Simheuristics for Optimizing Transportation Systems: Dealing with Stochastic and Fuzzy Uncertainty
by Rafael D. Tordecilla, Leandro do C. Martins, Javier Panadero, Pedro J. Copado, Elena Perez-Bernabeu and Angel A. Juan
Appl. Sci. 2021, 11(17), 7950; https://0-doi-org.brum.beds.ac.uk/10.3390/app11177950 - 28 Aug 2021
Cited by 10 | Viewed by 2500
Abstract
In the context of logistics and transportation, this paper discusses how simheuristics can be extended by adding a fuzzy layer that allows us to deal with complex optimization problems with both stochastic and fuzzy uncertainty. This hybrid approach combines simulation, metaheuristics, and fuzzy [...] Read more.
In the context of logistics and transportation, this paper discusses how simheuristics can be extended by adding a fuzzy layer that allows us to deal with complex optimization problems with both stochastic and fuzzy uncertainty. This hybrid approach combines simulation, metaheuristics, and fuzzy logic to generate near-optimal solutions to large scale NP-hard problems that typically arise in many transportation activities, including the vehicle routing problem, the arc routing problem, or the team orienteering problem. The methodology allows us to model different components–such as travel times, service times, or customers’ demands–as deterministic, stochastic, or fuzzy. A series of computational experiments contribute to validate our hybrid approach, which can also be extended to other optimization problems in areas such as manufacturing and production, smart cities, telecommunication networks, etc. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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18 pages, 1571 KiB  
Article
Fuzzy Logic Approach for Maximum Power Point Tracking Implemented in a Real Time Photovoltaic System
by Cristian Napole, Mohamed Derbeli and Oscar Barambones
Appl. Sci. 2021, 11(13), 5927; https://0-doi-org.brum.beds.ac.uk/10.3390/app11135927 - 25 Jun 2021
Cited by 15 | Viewed by 2153
Abstract
Photovoltaic (PV) panels are devices capable of converting solar energy to electrical without emissions generation, and can last for several years as there are no moving parts involved. The best performance can be achieved through maximum power point tracking (MPPT), which is challenging [...] Read more.
Photovoltaic (PV) panels are devices capable of converting solar energy to electrical without emissions generation, and can last for several years as there are no moving parts involved. The best performance can be achieved through maximum power point tracking (MPPT), which is challenging because it requires a sophisticated design, since the solar energy fluctuates throughout the day. The PV used in this research provided a low output voltage and, therefore, a boost-converter with a non-linear control law was implemented to reach a suitable end-used voltage. The main contribution of this research is a novel MPPT method based on a voltage reference estimator (VRE) combined with a fuzzy logic controller (FLC) in order to obtain the maximum power from the PV panel. This structure was implemented in a dSpace 1104 board for a commercial PV panel, PEIMAR SG340P. The scheme was compared with a conventional perturbation and observation (P&O) and with a sliding mode controller (SMC), where the outcomes demonstrated the superiority of the proposed advanced method. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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27 pages, 1284 KiB  
Article
Multidimensional Type 2 Epistemic Fuzzy Arithmetic Based on the Body Definition of the Type 2 Fuzzy Set
by Andrzej Piegat and Marek Landowski
Appl. Sci. 2021, 11(13), 5844; https://0-doi-org.brum.beds.ac.uk/10.3390/app11135844 - 23 Jun 2021
Cited by 4 | Viewed by 1172
Abstract
The article presents a multidimensional type 2 epistemic fuzzy arithmetic (MT2EF-arithmetic) based on the new body definition of fuzzy set type 2 (T2FS), which in the authors’ opinion, is more suitable for fuzzy computing than the current versions of fuzzy arithmetic (FA) based [...] Read more.
The article presents a multidimensional type 2 epistemic fuzzy arithmetic (MT2EF-arithmetic) based on the new body definition of fuzzy set type 2 (T2FS), which in the authors’ opinion, is more suitable for fuzzy computing than the current versions of fuzzy arithmetic (FA) based on the border definition of T2FS. The proposed MT2EF-arithmetic is designed for epistemic variables and has mathematical properties that allow for obtaining universal algebraic calculation results. MT2EF-arithmetic performs calculations, not only with borders of fuzzy numbers, but also with whole bodies of FNs. Thanks to this, computational tasks are solved in the full space of the problem and not in a limited, low-dimensional space. As a result, MT2EF-arithmetic provides precise solutions to problems, solutions that are neither overestimated, underestimated, nor shifted. The paper contains an example of MT2EF-application to optimal fertilization of beetroot cultivation with nitrogen. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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19 pages, 5368 KiB  
Article
Fuzzy-Based Quality Adaptation Algorithm for Improving QoE from MPEG-DASH Video
by Waqas ur Rahman, Md Delowar Hossain and Eui-Nam Huh
Appl. Sci. 2021, 11(11), 5270; https://0-doi-org.brum.beds.ac.uk/10.3390/app11115270 - 06 Jun 2021
Cited by 3 | Viewed by 1931
Abstract
Video clients employ HTTP-based adaptive bitrate (ABR) algorithms to optimize users’ quality of experience (QoE). ABR algorithms adopt video quality based on the network conditions during playback. The existing state-of-the-art ABR algorithms ignore the fact that video streaming services deploy segment durations differently [...] Read more.
Video clients employ HTTP-based adaptive bitrate (ABR) algorithms to optimize users’ quality of experience (QoE). ABR algorithms adopt video quality based on the network conditions during playback. The existing state-of-the-art ABR algorithms ignore the fact that video streaming services deploy segment durations differently in different services, and HTTP clients offer distinct buffer sizes. The existing ABR algorithms use fixed control laws and are designed with predefined client/server settings. As a result, adaptation algorithms fail to achieve optimal performance across a variety of video client settings and QoE objectives. We propose a buffer- and segment-aware fuzzy-based ABR algorithm that selects video rates for future video segments based on segment duration and the client’s buffer size in addition to throughput and playback buffer level. We demonstrate that the proposed algorithm guarantees high QoE across various video player settings and video content characteristics. The proposed algorithm efficiently utilizes bandwidth in order to download high-quality video segments and to guarantee high QoE. The results from our experiments reveal that the proposed adaptation algorithm outperforms state-of-the-art algorithms, providing improvements in average video rate, QoE, and bandwidth utilization, respectively, of 5% to 18%, about 13% to 30%, and up to 45%. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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11 pages, 1020 KiB  
Article
Fuzzy Evaluation Model of Process Improvement Capability with Costs Consideration
by Kuen-Suan Chen, Shui-Chuan Chen, Ting-Hsin Hsu, Min-Yi Lin and Chih-Feng Wu
Appl. Sci. 2021, 11(10), 4344; https://0-doi-org.brum.beds.ac.uk/10.3390/app11104344 - 11 May 2021
Cited by 1 | Viewed by 1307
Abstract
The Taguchi capability index, which reflects the expected loss and the yield of a process, is a useful index for evaluating the quality of a process. Several scholars have proposed a process improvement capability index based on the expected value of the Taguchi [...] Read more.
The Taguchi capability index, which reflects the expected loss and the yield of a process, is a useful index for evaluating the quality of a process. Several scholars have proposed a process improvement capability index based on the expected value of the Taguchi loss function as well as the corresponding cost of process improvement. There have been a number of studies using the Taguchi capability index to develop suppliers’ process quality evaluation models, whereas models for evaluating suppliers’ process improvement potential have been relatively lacking. Thus, this study applies the process improvement capability index to develop an evaluation model of the supplier’s process improvement capability, which can be provided to the industry for application. Besides, owing to the current need to respond quickly, coupled with cost considerations and the limits of technical capabilities, the sample size for sampling testing is usually not large. Consequently, the evaluation model of the process improvement capability developed in this study adopts a fuzzy testing method based on the confidence interval. This method reduces the risk of misjudgment due to sampling errors and improves the testing accuracy because it can incorporate experts and their accumulated experiences. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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18 pages, 12294 KiB  
Article
Classification with Fuzzification Optimization Combining Fuzzy Information Systems and Type-2 Fuzzy Inference
by Martin Tabakov, Adrian Chlopowiec, Adam Chlopowiec and Adam Dlubak
Appl. Sci. 2021, 11(8), 3484; https://0-doi-org.brum.beds.ac.uk/10.3390/app11083484 - 13 Apr 2021
Cited by 11 | Viewed by 2931
Abstract
In this research, we introduce a classification procedure based on rule induction and fuzzy reasoning. The classifier generalizes attribute information to handle uncertainty, which often occurs in real data. To induce fuzzy rules, we define the corresponding fuzzy information system. A transformation of [...] Read more.
In this research, we introduce a classification procedure based on rule induction and fuzzy reasoning. The classifier generalizes attribute information to handle uncertainty, which often occurs in real data. To induce fuzzy rules, we define the corresponding fuzzy information system. A transformation of the derived rules into interval type-2 fuzzy rules is provided as well. The fuzzification applied is optimized with respect to the footprint of uncertainty of the corresponding type-2 fuzzy sets. The classification process is related to a Mamdani type fuzzy inference. The method proposed was evaluated by the F-score measure on benchmark data. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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28 pages, 6965 KiB  
Article
Optimizing Design of Smart Workplace through Multi-Objective Programming
by Shady Aly, Jan Tyrychtr and Ivan Vrana
Appl. Sci. 2021, 11(7), 3042; https://0-doi-org.brum.beds.ac.uk/10.3390/app11073042 - 29 Mar 2021
Cited by 3 | Viewed by 1773
Abstract
Smart environments have proven very supportive to the improvement of the performance of people in different workplaces. Plenty of applications have been introduced spanning different settings including healthcare, ambient assisted living, homes, offices, and manufacturing environment, etc. However, subjectivity and ambiguity prevail in [...] Read more.
Smart environments have proven very supportive to the improvement of the performance of people in different workplaces. Plenty of applications have been introduced spanning different settings including healthcare, ambient assisted living, homes, offices, and manufacturing environment, etc. However, subjectivity and ambiguity prevail in the majority of research, and still, up to date, rare approaches found quantitatively and objectively constructing or assessing the impact of smart enabling technologies on the performance of the subject environment. Further, no approaches have considered optimizing the adoption of those smart technologies with respect to objectives achievement. This article presents a novel optimization methodology for designing a smart workplace environment in conditions of ambiguity or fuzziness. The methodology begins with defining and weighing the overall goals and objectives of the workplace. The Prometthe multi-criterion decision-making technique is used to weigh the operational objectives with respect to the overall workplace goals. Next, the relation among basic building blocks of the model; namely: the operational objectives, smartness features, and smart enabling technologies are quantified, utilizing fuzzy relations. Then, the fuzzy goal programming techniques will be utilized to optimize the impact relation values while considering the budget constraint. The proposed optimization methodology is implemented on the development and optimization of the smart clinic, as a typical instance of the workplace. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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26 pages, 5409 KiB  
Article
Design of a Fuzzy Optimization Control Structure for Nonlinear Systems: A Disturbance-Rejection Method
by Samia Charfeddine, Attia Boudjemline, Sondess Ben Aoun, Houssem Jerbi, Mourad Kchaou, Obaid Alshammari, Zied Elleuch and Rabeh Abbassi
Appl. Sci. 2021, 11(6), 2612; https://0-doi-org.brum.beds.ac.uk/10.3390/app11062612 - 15 Mar 2021
Cited by 9 | Viewed by 1666
Abstract
This paper tackles the control problem of nonlinear disturbed polynomial systems using the formalism of output feedback linearization and a subsequent sliding mode control design. This aims to ensure the asymptotic stability of an unstable equilibrium point. The class of systems under investigation [...] Read more.
This paper tackles the control problem of nonlinear disturbed polynomial systems using the formalism of output feedback linearization and a subsequent sliding mode control design. This aims to ensure the asymptotic stability of an unstable equilibrium point. The class of systems under investigation has an equivalent Byrnes–Isidori normal form, which reveals stable zero dynamics. For the case of modeling uncertainties and/or process dynamic disturbances, conventional feedback linearizing control strategies may fail to be efficient. To design a robust control strategy, meta-heuristic techniques are synthesized with feedback linearization and sliding mode control. The resulting control design guarantees the decoupling of the system output from disturbances and achieves the desired output trajectory tracking with asymptotically stable dynamic behavior. The effectiveness and efficiency of the designed technique were assessed based on a benchmark model of a continuous stirred tank reactor (CSTR) through numerical simulation analysis. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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15 pages, 1016 KiB  
Article
Multiple-Criteria Fuzzy Optimization of the Heat Treatment Processes for Two Steel Rolled Products
by Ludmila Dymova, Krzysztof Kaczmarek and Pavel Sevastjanov
Appl. Sci. 2021, 11(5), 2324; https://0-doi-org.brum.beds.ac.uk/10.3390/app11052324 - 05 Mar 2021
Cited by 4 | Viewed by 1351
Abstract
This paper presents a developed method for fuzzy multiple-criteria optimization of the rolled-steel heat treatment processes in the modern metallurgical plant. At the first stage of the study, by means of passive industrial experiments or a mathematical simulation of heat transfer processes, and [...] Read more.
This paper presents a developed method for fuzzy multiple-criteria optimization of the rolled-steel heat treatment processes in the modern metallurgical plant. At the first stage of the study, by means of passive industrial experiments or a mathematical simulation of heat transfer processes, and using statistical methods, the regression dependencies of the output parameters of process quality on the input variables that are technological parameters are established. Then, based on the quality parameters, membership functions are formed that represent local criteria of the process quality, and their ranks are calculated using the matrix of pairwise comparisons. The practically useful methodology of the fuzzy multiple-criteria optimization of technological processes is proposed. To illustrate this methodology’s practical efficiency, the solutions of two optimization problems are found by maximizing the global criterion that aggregates local criteria using their ranks. It is shown that the efficiency of the obtained optimal heat treatment modes significantly exceeds the efficiency of the technology used earlier in the plant. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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19 pages, 631 KiB  
Article
A Hybrid Fuzzy TOPSIS Method to Analyze the Coverage of a Hypothetical EU Ecolabel for Fishery and Aquaculture Products (FAPs)
by Javier Cantillo, Juan Carlos Martín and Concepción Román
Appl. Sci. 2021, 11(1), 112; https://0-doi-org.brum.beds.ac.uk/10.3390/app11010112 - 24 Dec 2020
Cited by 7 | Viewed by 2223
Abstract
This study presents a hybrid fuzzy technique for order preference by similarity of the ideal solution (TOPSIS) method (FTOPSIS) to analyze the coverage of a hypothetical EU ecolabel for fishery and aquaculture products (FAPs) by integrating a synthetic indicator to determine the level [...] Read more.
This study presents a hybrid fuzzy technique for order preference by similarity of the ideal solution (TOPSIS) method (FTOPSIS) to analyze the coverage of a hypothetical EU ecolabel for fishery and aquaculture products (FAPs) by integrating a synthetic indicator to determine the level of acceptance for the inclusion of different types of information apart from environmental issues, considering different stakeholders and other segments of analysis. Data were obtained from a public consultation of the EU on “ecolabels for FAPs”. The results indicate that ecolabels should not only include environmental issues but also other types of information, with social and ethical issues being the most relevant, followed by animal welfare issues, health and safety issues and food quality issues. The findings also show that consumers, producers and stakeholders who are more interventionist and support the fact that public bodies and governments should be involved in the control of eco-labeling are more accepting of including additional information apart from environmental issues. Synthetic indicators (SIs) have also been found to be mostly inelastic, except for the owners of ecolabels on social and ethical issues. The implications of the future implementation of the EU ecolabel for FAPs are discussed based on the findings. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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