Interval Type-2 Fuzzy Technique Research Articles

A Decision Support System Based on Hybrid Approach With Copras And Interval Type-2 Fuzzy Topsis For Evaluation Of Renewable Energy Alternatives

Renewable energy (RE) is a vital source for the sustainable development of society and economy. It plays a significant role in meeting energy requirements of both developed and developing countries. Moreover, renewable energy creats multiple benefits such as environmental improvement, increases fuel diversity, reduction of energy price, volality effect on their economy, national economic security, and increases in economic productivity. Selection of the most appropriate RE alternatives for any country can provide guidelines to planners of regional, national and global energy systems. The issue of ranking renewable energy sources involves many conflicting criteria and is a complicated problem since it needs to simultaneously incorporate technical, economic, cost, social-political, and environmental criteria. In this study, an integrated multi criteria decision making (MCDM) aproach consisting of interval type-2 fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Compressed Proportional Assessment (COPRAS) method is conducted to prioritize RE alternatives in order to direct planning of the national RE investments. A real case application for Turkey has been presented via expert evaluations to demonstrate applicability of the proposed methodology.

Research on the location decision-making method of emergency medical facilities based on WSR

The need for emergency medical services increased drastically during disaster relief. Poor location selection of emergency medical facilities may harm the interests of healthcare workers and patients, leading to unnecessary waste of costs. It involves multiple stakeholders' interests, a typical multi-criteria decision-making problem. Based on multiple-criteria decision-making technology, most current location selection decisions methods comprehensively consider the evaluation criteria of "issue" and "problem" simultaneously and establish mathematical models to achieve the results. Such methods are difficult to take into account the influence of different attribute factors on the final location selection results in practice. Therefore, in this study, we used the WSR methodology as a guide to divide the factors of location selection into "Wuli", "Shili" and "Renli", and proposed the WSR methodology-based multi-criteria decision‐making (MCDM) framework for selecting the appropriate location for emergency medical facilities. The integrated framework consists of the Entropy Weight Method, Best–Worst Method, and interval type‐2 fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies. Combined with the comparative analysis of actual cases, the results under the guidance of this framework were consistent with practicalities. Also, the sensitivity analysis showed that the location selection ranking fluctuations were not apparent with the fluctuation of criteria weights. Wherefore, the validation of the proposed method's effectiveness, feasibility, and robustness was proved, which provided a valuable reference for the location selection of emergency medical facilities.

Composite fault reconstruction and fault-tolerant control design for cyber-physical systems: An interval type-2 fuzzy approach

This article scrutinizes the stabilization and fault reconstruction issues for interval type-2 fuzzy-based cyber–physical systems with actuator faults, deception attacks and external disturbances. The primary objective of this research is to formulate the learning observer system with the interval type-2 fuzzy technique that reconstructs the actuator faults as well as the immeasurable states of the addressed fuzzy based model. Further, the information of reconstructed actuator faults is incorporated in the developed controller with the imperfect premise variables for ensuring the stabilization of the system under consideration. At the same time, the H∞ technique is employed to reduce the impact of external disturbances in the considered model. In addition to that, the deception attacks are represented as a stochastic variable that satisfies the Bernoulli distributions. On the ground of this, a set of sufficient criteria is deduced in the context of linear matrix inequalities to affirm the stability of the addressed systems. Furthermore, the requisite gain matrices are computed by resolving the obtained linear matrix inequality based stability criteria. At last, two simulation examples, including the mass–spring–damper system are exhibited to demonstrate the usefulness of analytical findings of the developed strategy.

An Improved Lifetime and Energy Consumption with Enhanced Clustering in WSNs

A wireless sensor network (WSN) is made up of sensor nodes that communicate via radio waves in order to conduct sensing functions. In WSN, the location of the base station is critical. Although base stations are fixed, they may move in response to data received from sensor nodes under specific conditions. Clustering is a highly efficient approach of minimising energy use. The issues of extending the life of WSNs and optimising their energy consumption have been addressed in this paper. It has been established that integrating mobile sinks into wireless sensor networks extends their longevity. Thus, this research proposes an optimal clustering and routing technique for optimising the energy usage and lifetime of WSNs. To minimise energy consumption, this research employs movable and stationary sink nodes. The K-Medoid clustering model is used to generate the initial number of nodes in the various clusters. After that, the cluster head is chosen using a hybrid Interval Type-2 Fuzzy technique that takes three aspects into account: residual energy, node centrality, and neighbourhood. A highly efficient backup cluster head (CH) collecting system can provide in significant energy savings while also prolonging the system’s life. Finally, better Reinforcement learning combined with a Genetic algorithm routing protocol is used to ensure effective data delivery. The suggested approach’s efficacy is evaluated in comparison to earlier approaches utilising residual node energy, delay or average delay, packet delivery ratio, throughput, network longevity, average energy consumption, and multiple alive nodes. In experiments, the proposed strategy outperforms existing strategies.

MALE UAV selection in interval Type-2 fuzzy sets environment

Unmanned Aerial Vehicles (UAVs) are increasingly used in the military field. Especially in recent years, UAVs have been a very effective instrument in gaining airspace superiority and military success. Many countries compete with each other to develop better UAV technology or improve the technical features of UAVs. Therefore, it is critical to determine which UAV has the best performance, considering technical and operational characteristics, because the vehicles with more advanced performance can provide countries with strategic superiority. The purpose of this study is to investigate the technical, cost, and operational performance of Medium Altitude Long Endurance UAVs (MALE UAVs). In the study, as a result of a wide literature review, we determined a performance criterion for this type of vehicle. The model presented here uses an Interval Type-2 Fuzzy Analytical Hierarch Process (IT2FAHP) and an Interval Type-2 Fuzzy Technique for Order of Preference by Similarity to an Ideal Solution (IT2FTOPSIS) hybrid method. The findings indicate that some MALE UAVs have superior technical and operational performance over others and demonstrate that range, max take-off weight, and payload are important criteria in determining the performance and superiority of these vehicles.

An integrated interval type-2 fuzzy technique for democratic–autocratic​ multi-criteria decision making

This paper develops an integrated trapezoidal interval type-2 fuzzy (TrIT2F) technique for democratic–autocratic multi-criteria group decision making based on best–worstmethod (BWM) and VIKOR (VIsekriterijumska optimizacija i KOm-promisno Resenje), which is called TrIT2F-BW-VIKOR. In this technique, the pairwise comparisons and evaluations are represented by trapezoidal interval type-2 fuzzy sets (TrIT2FSs). The existing definition of TrIT2FS is perfected by adding two rational constraints proposed in this paper. A weight-normalizing theorem is initiated to normalize the TrIT2F weights. To determine the TrIT2F weights of junior decision makers (JDMs) and criteria, the classical BWM is extended into TrIT2F environment, which is called TrIT2F-BWM. In this TrIT2F-BWM, the weight-normalizing theorem is applied to normalize the TrIT2F weights, a consistency ratio is designed to check the reliability of the obtained TrIT2F weights. Based on the determined weights of JDMs and criteria, an extended VIKOR is developed to rank alternatives. The proposed technique can not only effectively retain the inherent fuzzy information of TrIT2FSs, but also flexibly handle different decision situations. The validity of the proposed technique is demonstrated with a makeshift (fangcang) hospital selection example on COVID-19. Some sensitivity and comparison analyses are provided to show the stability, flexibility, and superiorities of the proposed technique.

A Regret-Based Three-Way Decision Model Under Interval Type-2 Fuzzy Environment

Three-way decision provides a new perspective for dealing with uncertainty and complexity in decision-making problems. However, behaviors of decision-makers may be influenced by different risk attitudes in reality. To address this problem, in this article, we construct a regret-based three-way decision model under interval type-2 fuzzy environment. Basically, regret theory and interval type-2 fuzzy set are utilized to improve three-way decision in coping with the risk and uncertainty. Two core issues focus on the determination of decision rules and estimation of conditional probabilities for different decision-makers under interval type-2 fuzzy environment. The maximum-utility decision rules are derived based on regret theory. An interval type-2 fuzzy technique for order preference by similarity to ideal solution method is utilized to estimate the conditional probability. The results of the illustrative example show that the proposed model can effectively solve uncertain decision problems. The comparative analysis and experimental evaluations are utilized to elaborate on the performance of the regret-based three-way decision model.

Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets

The selection of the appropriate aircraft can bring competitive advantages to airlines, however, there are a number of factors which introduce a degree of uncertainty to the selection process. By removing this uncertainty, airlines can increase their chances of achieving their long-term goals. New Multi-Criteria Decision Making (MCDM) methods provide decision-makers with a satisfactory solution for choosing suitable aircraft. Therefore, we focused on the multi-dimensional evaluation and selection of the most suitable commercial aircraft alternatives by using new MCDM method. This article provides decision support to airline planners on the selection of commercial aircraft under uncertainty. In the study, unlike other studies in the literature on aircraft selection, the model presented here uses an Interval Type-2 Fuzzy Analytical Hierarch Process (IT2FAHP) and Interval Type-2 Fuzzy Technique for Order Preference by Similarity to an Ideal Solution (IT2FTOPSIS) hybrid methods. The proposed model for aircraft selection allows commercial airlines to evaluate the aircraft in terms of specific criteria: economic performance, technical performance, and environmental impact, and, as a result, it helps decision makers select appropriate aircraft in an uncertain environment. In addition to use by commercial airlines, the methods in the study can also be applied to the selection of training aircraft, cargo aircraft and military aircraft. Our findings show that the Airbus A321neo is the most suitable commercial aircraft in terms of technical aspects, economic aspects and environmental aspects for airlines.

Analysis of spiritual leadership and ethical climate for banking industry using an integrated IT2 fuzzy decision-making model

The study aims to propose a novel model to define the role of spiritual leadership on the ethical climate for the banking industry. There are mainly three different stages in this model. Firstly, the criteria of each factor are selected with correlation coefficients by considering the balanced scorecard (BSC)-based linguistic evaluations. After that, these criteria are weighted by using interval type-2 (IT2) fuzzy decision-making trial and evaluation laboratory (DEMATEL). The third and the final stage aims to rank 5 biggest banks of Turkey which are quoted in İstanbul Stock Exchange. Within this framework, IT2 fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach is considered. The findings demonstrate that the spiritual leadership has a significant influence on the ethical climate. Altruistic love is the most important spiritual leadership dimension to improve ethical climate in the organization. On the other side, it is also concluded that private banks in Turkey are the most successful with respect to the ethical climate. The results give an idea that spiritual leader contributes to the improvement of the ties of love and respect among employees. The main reason is that altruistic love improves the judgement and sensitivity competencies of the ethical so that employees tend to be working in a more ethical way.

Sustainability performance assessment of wind power coupling hydrogen storage projects using a hybrid evaluation technique based on interval type-2 fuzzy set

The purpose of this study is to assess the performance of wind power coupling hydrogen storage projects from the perspective of sustainability. Firstly, an evaluation criteria system for sustainability performance assessment is established, which includes economic, environmental and social aspects. Then, the criteria performances of each alternative are determined by expert groups in the fields of energy economy, energy environment and society sciences. Later, considering the uncertainty in the decision-making, the interval type-2 fuzzy Analytic Hierarchy Process and the interval type-2 fuzzy Technique for Order Preference by Similarity to an Ideal Solution technique are employed to weight the criteria and sort the alternatives, respectively. Finally, a case study in Tibet autonomous, China is given to illustrate the effective of the proposed evaluation criteria and technique. The result shows the alternatives A4 gets the highest score. Moreover, the results of sensitivity analysis reveal that the alternative A4 always secures its top ranking when its weight is floating within a certain range. Meanwhile, the weight results show that the criteria of levelized cost of energy and poverty alleviation promotion should gain more attention. This research can offer references for investors to make investment decisions and for the government to make corresponding policies.

An Integrated Best-Worst and Interval Type-2 Fuzzy TOPSIS Methodology for Green Supplier Selection

Supplier selection is one of the most important multi-criteria decision-making (MCDM) problems for decision-makers in the competitive market. Today’s organizations are seeking new ways to reduce the negative effects they have on the environment and to achieve a greener system. Currently, the concept of green supplier selection has gained great importance for its ability to incorporate environmental or green criteria into classical supplier selection practices. Therefore, in this study, a multi-phase MCDM model based on the best-worst method (BWM) and the interval type-2 fuzzy technique for order preference by similarity to ideal solution (IT2F TOPSIS) is proposed. A case study in a plastic injection molding facility in Turkey was carried out to show the applicability of the proposed integrated methodology. The paper offers insights into decision-making, methodology, and managerial implications. Results of the case study are examined and suggestions for future research are provided.

Interval type-2 fuzzy TOPSIS method for calibration supplier selection problem: a case study in an automotive company

Product standardization has gained importance with the increase of customer demands and developments of technology. Products must be tested with measurement equipment to ensure quality standards. In quality management, the variability between products is targeted to be minimum. Products are produced at a target value with specific tolerance levels. Measurement equipment are used to confirm that the dimensions be in accordance with the required tolerance levels. The calibration of measurement equipment is crucial for acquiring certain measurements. The calibration process aims to minimize the measurement error by providing the accuracy of measurement equipment. The companies can carry out their calibration processes in the company structure for certain equipment. However, companies may need outsourcing for the calibration of complex equipment. This study includes a model to select the most appropriate calibration supplier by using the interval type-2 fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method. The proposed approach is presented with a case study for torque-limiting wrench calibration in an automotive company. In the case study, ten different evaluation criteria were determined from the decision-makers and the literature for the calibration suppliers’ evaluation and selection. Within the scope of these criteria, three alternative suppliers (A, B, and C) were evaluated and supplier C was selected as the most suitable calibration supplier.

An interval type-2 fuzzy technique for order preference by similarity to ideal solutions using a likelihood-based comparison approach for multiple criteria decision analysis

The technique for order preference by similarity to ideal solutions (TOPSIS) is a well-known compromising method for addressing decision-making problems. In general, incomplete preference information and vague subjective judgments are realistic in practice. Accordingly, the theory of interval type-2 fuzzy sets has received increasing attention in the decision-making field because of its great ability to handle imprecise and ambiguous information in a convenient manner. The purpose of this paper is to develop a novel interval type-2 fuzzy TOPSIS method for multiple criteria decision analysis that is based on interval type-2 trapezoidal fuzzy numbers. This paper introduces the concept of approximate positive-ideal and negative-ideal solutions and presents a simple way to approach the evaluative ratings of ideal solutions using interval type-2 trapezoidal fuzzy numbers. Based on the likelihoods of interval type-2 trapezoidal fuzzy binary relations, this paper proposes certain likelihood-based comparison indices to establish a likelihood-based closeness coefficient of each alternative relative to the approximate ideals. Applying a likelihood-based comparison approach with the approximate ideals, this paper develops the interval type-2 fuzzy TOPSIS procedure to determine the priority ranking orders of the alternatives under consideration of the multiple criteria evaluation/selection. Three practical applications involving landfill site selection, supplier selection, and car evaluation are examined to show the effectiveness and practicability of the proposed method. Furthermore, this paper makes a comparison of the solution results yielded by other interval type-2 fuzzy decision-making methods. The comparative analyses demonstrate that the proposed interval type-2 fuzzy TOPSIS method is easy to implement and produces effective and valid results for solving multiple criteria decision-making problems.

The Use of Interval Type-2 Fuzzy TOPSIS in Supplier Selection

Supplier selection is one of the most important activities in supply chain management. However, the method of selecting appropriate supplier is not straightforward as it involves number of potential suppliers with diverse criteria. This paper aims to select the best supplier using interval type-2 fuzzy Technique for Order Preference by Similarity to Ideal Solution (IT2FTOPSIS) method. The method is used to a case study of computer components supplier selection. Of the four candidate suppliers, it is found that the supplier S3 is the best candidate. It indicates that the IT2FTOPSIS method offers a feasible solution to supplier selection problem.