Iranian Journal of Fuzzy Systems
Year:2021 | Volume:18 | Issue:1|Papers Count:12

Generally, the criteria involved in a decision making problem are interactive or inter-dependent, and therefore aggregating them by the use of traditional operators which are based on additive measures is not logical. This verifies that we have to implement fuzzy measures for modelling the interaction phenomena among the criteria. On the other hand, based on the recent extension of hesitant fuzzy set, called higher order hesitant fuzzy set (HOHFS) which allows the membership of a given element to be defined in forms of several possible generalized types of fuzzy set, we encourage to propose the higher order hesitant fuzzy (HOHF) Choquet integral operator. This concept not only considers the importance of the higher order hesitant fuzzy arguments, but also it can reflect the correlations among those arguments. Then, a detailed discussion on the aggregation properties of the HOHF Choquet integral operator will be presented. To enhance the application of HOHF Choquet integral operator in decision making, we first assess the appropriate energy policy for the socio-economic development. Then, the efficiency of the proposed HOHF Choquet integral operator-based technique over a number of exiting techniques is further verified by employing another decision making problem associated with the technique of TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making).

The cross-migrativity has been investigated for families of certain aggregation operators, such as t-norms, t-subnorms and uninorms. In this paper, we aim to study the cross-migrativity property for semi-t-operators, which are generalizations of t-operators by omitting commutativity. Specifically, we give all solutions of the cross-migrativity equation for all possible combinations of semi-t-operators. Moreover, it is shown that if a semi-t-operator F is alpha-cross-migrative over another semi-t-operator G, then G must be a semi-nullnorm except one case. Finally, it is pointed out that the cross-migrativity property between two semi-t-operators is always determined by their underlying operators except a few cases.

This article deals with the problem H1 control under network T-S fuzzy system with random packet dropouts for the synchronous machine. In the control design, the intermittent data loss existing in the closed-loop system is taken into account. Two main approaches adopted in this paper to design the fuzzy controller. First, a new version of the T-S fuzzy state-feedback controller is constructed to guarantee the resulting closed-loop system to be stochastically stable. Furthermore, in this regard, by taking into account a new version of fuzzy Lyapunov-Krasovskii functional (LKF) in conjunction with free weighting matrices, containing mode-dependent non-integral term such that the resulting system is stochastically stable with the desired performance. Second, to establish the pole place method (PPM) with the membership function. Furthermore, to make the controller design more convenient, the designed controller does not need to share the number of fuzzy rules and membership functions with the model. Synchronous machine parameters are used for the simulation results which are provided to show the usefulness of the proposed algorithm.

This paper introduces a new decision support framework for transport projects appraisal, which is based on the multi-criteria decision analysis (MCDA) and the cost-benefit analysis (CBA) to address both monetary and non-monetary characteristics of the problem at the same time. Substantial inaccuracies are present while obtaining non-monetary and monetary inputs to the MCDA and the CBA, respectively. To provide the MCDA part of the framework with uncertainty, an interval-valued Pythagorean fuzzy set (IVPFS) is used as an attractive uncertain modeling tool. Additionally, a new multi-attribute group decision-making (MAGDM) method with partially known attribute weights and unknown expert weights under the IVPFS environment is proposed to find the best sustainable transport project from the non-monetary criteria point of view. Furthermore, a novel uncertainty modeling tool, namely an interval-valued Pythagorean trapezoidal fuzzy set, is introduced to address ill-known quantities and inaccuracies that exist in the estimation of monetary impacts. Finally, this framework is used to handle a real case study of a complex decision process of finding the best transport project to fund several candidate projects. This approach has made it possible to handle the decision process from economic, social, environmental points of view at the same time. The result of this case study shows that the decision-making framework can be used as a valuable decision support tool. Moreover, it is shown that the presented framework can be applied to effectively support appraisals of transport projects.

Fuzzy closure operators play a significant role in fuzzy order theory. This paper aims to further enrich and improve the study of fuzzy closure operators. Based on the work of Belohlá vek and Yao, we shall continue to study the relative properties of fuzzy closure operators. First, we shall consider the extensions of $L$-subsets via fuzzy closure operators. Then we give an application of fuzzy closure operators, that is, by fuzzy closure operators we shall prove that the category CFPos of complete fuzzy posets and their fuzzy-join preserving maps is a reflective full subcategory of FPos, where FPos denotes the category of fuzzy posets and their fuzzy-existing-join preserving maps.

Nowadays, some burgeoning issues occurring in green and sustainable supply chain face an increasing number of tackles, including uncertain factors and unobserved data, which makes it even more complicated to assess supply chain efficiency. To address this issue, this paper applies uncertainty theory to two-stage network DEA intending to deal with inaccurate data. Moreover, the bi-echelon supply chain generally suffers asymmetric power among involved members. Therefore, this paper proposes attrition rate (D) and fulfillment rate (G) in the first and second stages respectively so as to reveal the bi-echelon supply chain within different leader-follower patterns. The first two models assume the upstream firm is the leader while the last two models regard the downstream firm as the leader. We find out that the results of the evaluation vary under divergent patterns accordingly by running a numerical example. Adopting proposed models can help decision-makers of the multistage supply chain make decisions more effectively and avoid possible mistakes.

Research in the area of Internet of things (IoT) and cloud computing has gained a considerable attention in today's world of information technology (IT). Data compression and security are increasingly appreciated due to their imperative roles in online data sharing and transfer in multimedia networks. Hence, image compression is focused on reducing data redundancy and saving memory and transmission bandwidth. Because of the increased entropy of coded images, it is difficult to reduce the amount of lossless information after encryption using the existing methods. Accordingly, using the hybrid Huffman coding algorithm, it is possible to guarantee the security and verification of information. Therefore, an efficient compression method is proposed that combines fuzzy logic with Huffman coding. In this method, coding is based on Hoffman code, which is statistically independent and defines fuzzy logic-based weighting functions for the frequency of the existing symbols in data to generate efficient code for compression. Fuzzy logic is then coded to provide a secure information mapping on the information codes. In this proposed system, the key information is coded using the special key of that information and the data is embedded using the data encryption key and data in the receiver are decoded using the same key. Here, different compression techniques are compared with Huffman coding. The simulation is performed under matlab2017b software. The results show that a good compression rate is achieved, there is no significant difference between the decoded and original images and compression ratio in the image is increased to over 40%.

The purpose of this study is to develop a dairy global supply chain planning model in which operational and financial dimensions are appropriately integrated in order to adjust the credit sale strategy. In order to evaluate the financial performance of the dairy supply chain, economic value-added index and some financial ratios are used. The proposed model is compared to traditional approaches, which usually use the profit maximization as an objective function. Also, the amount of credit sales is considered as a decision variable for the first time in this research. The developed model utilized a new risk measure, i. e., the fuzzy CVaR, to cope with the uncertainty of the exchange rate and the quality and quantity of returned products. The effectiveness and efficiency of the proposed model are analyzed and assessed using the data of a real dairy supply chain. The analysis of results obtained from the developed fuzzy mathematical model shows an increase in profit and a reduction in semi-variance compared to previously developed models. Also, some numerical experiments analyses index and the impact of credit sales strategy.

A geometric programming problem subject to bipolar max-product fuzzy relation equation constraints is studied in this paper. Some necessary and sufficient conditions are given for its solution existence. A lower and upper bound on the solution set of its feasible domain is obtained. Some sufficient conditions are proposed to determine some its optimal components without its resolution. A modified branch-and-bound method is extended to solve the problem. Moreover, an efficient algorithm is proposed to solve the problem based on the simplification operations and the modified branch-and-bound method. Its computational complexity is carefully analyzed. Some examples are given to show the importance of the problem and to illustrate the process of the algorithm. Finally, an analytic and comparative study is done to show the efficiency of the simplification procedures.

Projects require proper control and management techniques to achieve their defined success criteria. Often projects end in longer periods and higher costs than planned. It is necessary to apply approaches that can keep the project close to its predefined goals and purposes. In this paper, a new framework is presented that is mainly concerned with properly managing project implementation and evaluation. In detail, the method has four main parts. First, a new mathematical programming is offered to address project scheduling. The results of project scheduling are then applied in a critical chain method based approach under interval type-2 fuzzy uncertainty in the second part to both enhance project scheduling and address uncertainty. The third part of the approach is developed to monitor the project implementation process, and new thresholds are defined to discuss corrective measures when necessary. Finally, the fourth part of the approach is designed to evaluate project implementation and reach an understanding of how the project is implemented. To display the applicability of the approach, a practical example is solved, and the process is step by step presented along with the comparative analysis.

This article presents a new robust adaptive sliding mode controller for a class of uncertain nonlinear systems whereas only the system output is measurable. Firstly, a robust adaptive fuzzy observer is designed for the system in order to estimate its state variables. The robust asymptotic convergence of the proposed observer is proven by Lyapunov direct method. Then based on the observation states, a robust adaptive sliding mode controller is suggested such that the closed loop system to be asymptotically stable. Robust asymptotic stability of the overall system suggested by the controller is also confirmed based on Lyapunov theory. Simulation results illustrate practicality and effectiveness of the proposed technique for controlling uncertain nonlinear systems.

This paper aims to establish the existence and uniqueness results for two kinds of implicit uncertain fractional integral equations with the fuzzy concept via the fixed point theorem and successive approximation method. Besides, we also present various Ulam-Hyers stability and Ulam-Hyers-Rassias stability results of two kinds of implicit fuzzy fractional integral equations. Finally, some examples are given to illustrate our main results.