A state of the art literature review of VIKOR and its fuzzy extensions on applications

Player selection in football by integrated SWARA-VIKOR methods under fuzzy environment

This study aims to provide an objective evaluation and selection of the most suitable players for the Turkish National Football Team by using multi-criteria decision-making methods, specifically Stepwise Weight Assessment Ratio Analysis (SWARA) and VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) based on neutrosophic numbers. In the initial step of the study, the important criteria for player selection were determined, and a total of 21 and 26 criteria were identified for goalkeeper and players, respectively. Agility, reflexes and jumping ability are very important for goalkeeper whereas marking, passing ability, agility, dribbling, and footwork are the most important criteria for players. The performances of the players were evaluated due to these criteria and finally the Turkish National Football Team was established scientifically because of the best player selection. This decision-making process will be more beneficial in making more informed and effective decisions in the national team's player selection process. The success of the team can be improved by providing an objective and systematic player selection approach.

A historical review and analysis on MOORA and its fuzzy extensions for different applications

Multi-criteria decision-making (MCDM) methods have been widely used among researchers to provide a trade-off solution between best and worst, considering conflicting criteria and sets of preferences. An efficient and systematic literature review of these methods is needed to maintain their application in distinctive domains. To this end, this paper presents a comprehensive and systematic literature survey on "multi-objective optimization by ratio analysis" (MOORA) method and its fuzzy extensions developed and discussed in recent years. This review includes articles categorized based on the publication name, publishing year, journal name, type of applications, and type of fuzzy extensions. In addition, this review will enhance the understanding of practitioners and decision-makers on the MOORA method, its development, fuzzy hybridization, different application areas, and future work. The study revealed that the MOORA technique was predominantly used with the TOPSIS approach, followed by the AHP and COPRAS methods. Furthermore, 76.28 % use single and hybridization approaches among all MOORA studies, while 23.72 % use MOORA in a fuzzy environment.

Dental Material Selection for the Additive Manufacturing of Removable Complete Dentures (RCD)

This research addresses the development of a formalized approach to dental material selection (DMS) in manufacturing removable complete dentures (RDC). Three types of commercially available polymethyl methacrylate (PMMA) grades, processed by an identical Digital Light Processing (DLP) 3D printer, were compared. In this way, a combination of mechanical, tribological, technological, microbiological, and economic factors was assessed. The material indices were calculated to compare dental materials for a set of functional parameters related to feedstock cost. However, this did not solve the problem of simultaneous consideration of all the material indices, including their significance. The developed DMS procedure employs the extended VIKOR method, based on the analysis of interval quantitative estimations, which allowed the carrying out of a fully fledged analysis of alternatives. The proposed approach has the potential to enhance the efficiency of prosthetic treatment by optimizing the DMS procedure, taking into consideration the prosthesis design and its production route.

A new approach for spherical fuzzy TOPSIS and spherical fuzzy VIKOR applied to the evaluation of hydrogen storage systems

This study proposes a new perspective of the TOPSIS and VIKOR methods using the recently introduced spherical fuzzy sets (SFSs) to handle the vagueness in subjective data and the uncertainties in objective data simultaneously. When implementing these techniques using SFSs, two main problems might arise that can lead to incorrect results. Firstly, the reference points might change with the utilized score function. Secondly, the distance between reference points might not be the largest, as known, among the available ratings. To overcome these deficiencies and increase the robustness of these two methods, they are implemented without utilizing any reference points to minimize the effect of defuzzification and without measuring the distance to eliminate the effect of distance formulas. In the proposed methods, when using an SFS to express the performance of an alternative for a criterion, this SFS per se can be viewed as a measure of proximity to the aspired level. On the other hand, the conjugate of the SFS can be viewed as a measure of proximity to the ineffectual level. Two practical applications are presented to demonstrate the proposed techniques. The first example handles a warehouse location selection problem. The second example evaluates hydrogen storage systems for automobiles with different types of data (crisp, linguistic variables, type 1 fuzzy sets). These data are transformed to SFSs to provide a more comprehensive analysis. A comparative study is conducted with earlier versions of TOPSIS and VIKOR to explicate the adequacy of the proposed methods and the consistency of the results.

Research on the evaluation method of agricultural intelligent robot design solutions

BACKGROUND

At present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growth information. The scientific and rational design of agricultural robots plays a huge role in planting and production efficiency, however, the factors affecting their design are complex and ambiguous, so it is necessary to use a rational evaluation system to make a preferential decision among multiple design options.

PURPOSES

In order to reduce the subjectivity and blindness of program selection in the process of agricultural robot design, make the decision more objective and reasonable, and thus enhance the practicality and scientificity of the program, a new comprehensive evaluation method based on user requirements is proposed.

METHODS

First, after researching and interviewing users and farming operations, obtaining raw information on requirements, using the Kano model to classify the requirements and establishing an evaluation index system. Secondly, the combination of hierarchical analysis(AHP) and entropy weighting method is used to assign weights to the evaluation index system, calculate the weight value and importance ranking of each index, and carry out various program designs based on the ranking. Finally, the VIKOR method was applied to evaluate and rank the design solutions.

RESULTS

The new evaluation method can better complete the preferential decision of the agricultural robot design scheme and get a more perfect design scheme, which reduces the influence of human subjective thinking in the decision-making process.

CONCLUSIONS

The method not only corrects the traditional evaluation method, but also effectively improves the accuracy and comprehensiveness of the design evaluation process. It also provides a reference for designers to preferably select design solutions and promotes the development of small mobile machines in the context of smart agriculture.

Mitigating virus spread through dynamic control of community-based social interactions for infection rate and cost

The emergence of a new virus in a community may cause significant overload on health services and may spread out to other communities quickly. Social distancing may help reduce the infection rate within a community and prevent the spread of the virus to other communities. However, social distancing comes at a cost; how to strike a good balance between reduction in infection rate and cost of social distancing may be a challenging problem. In this paper, this problem is formulated as a bi-objective optimization problem. Assuming that in a community-based society interaction links have different capacities, the problem is how to determine link capacity to achieve a good trade-off between infection rate and the costs of social distancing restrictions. A standard epidemic model, Susceptible-Infected-Recovered, is extended to model the spread of a virus in the communities. Two methods are proposed to determine dynamically the extent of contact restriction during a virus outbreak. These methods are evaluated using two synthetic networks; the experimental results demonstrate the effectiveness of the methods in decreasing both infection rate and social distancing cost compared to naive methods.

A VIKOR-based approach to evaluate river contamination risks caused by wastewater treatment plant discharges

Wastewater treatment plants (WWTPs) rarely eliminate emerging contaminants from effluents they discharged into waterways, and therefore, represent significant contaminations sources with deleterious environmental risks. This paper presents a VIKOR-based model to assess the contamination risk posed by a cluster of WWTPs. A risk index was defined via building a membership function embodying the performance degrees of WWTPs and risks levels within the framework of fuzzy set theory. The proposed approach was tested using a case study of WWTPs cluster along the Pearl River. Sensitivity analyses were carried out to investigate the robustness of the model. The results confirmed the ability of the proposed approach to reveal the risk level of a given treatment point. Further, the comparison with a TOPSIS scheme as well as sensitivity analysis results substantiate the consistency, accuracy, and reliability of the proposed approach. It is therefore bounds to improve the decentralized management of WWTPs-induced river contamination.

Control measure prioritization in Fine - Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station

The Fine - Kinney is a risk assessment method widely used in many industries due to its ease of use and quantitative risk evaluation. As in other methods, it is a method that recommends taking a series of control measures for operational safety. However, it is not always possible to implement control measures based on the determined priorities of the risks. It is considered that determining the priorities of these measures depends on many criteria such as applicability, functionality, performance, and integrity. Therefore, this study has studied the prioritization of control measures in Fine - Kinney-based risk assessment. The criteria affecting the prioritization of control measures are hierarchically structured, and the importance weights of the criteria are determined by the Bayesian Best-Worst Method (BBWM). The priorities of control measures were determined with the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) method. The proposed model has been applied to the risk assessment process in a petrol station's liquid fuel tank area. According to the results obtained with BBWM, the most important criterion affecting the prioritization of control measures is the applicability criterion. It has an importance weight of about 42%. It is followed by performance with 31%, functionality with 18%, and integrity with 10%, respectively. FVIKOR results show that the "Periodic control of the ventilation device" measure is the top priority for Fine - Kinney risk assessment. "The absence of any ducts or sewer pits that may cause gas accumulation in the tank area and near the dispenser; Yellow line marking of entry and exit and vehicle roads; Placing of speed limit warning signs" has been determined as a secondary priority. On conclusion, this proposed model is expected to bring a new perspective to the work of occupational health and safety analysts, since the priority suggested by Fine - Kinney risk analysis methods is not always in the same order as the one in the stage of taking action, and the source, budget, and cost/benefit ratio of the measure affect this situation in practice.

An integrated expert weight determination method for design concept evaluation

Expert weight determination is a critical issue in the design concept evaluation process, especially for complex products. However, this phase is often ignored by most decision makers. For the evaluation of complex product design concepts, experts are selected by clusters with different backgrounds. This work proposes a novel integrated two-layer method to determine expert weight under these circumstances. In the first layer, a hybrid model integrated by the entropy weight model and the Multiplicative analytical hierarchy process method is presented. In the second layer, a minimized variance model is applied to reach a consensus. Then the final expert weight is determined by the results of both layers. A real-life example of cruise ship cabin design evaluation is implemented to demonstrate the proposed expert weight determination method. To analyze the feasibility of the proposed method, weight determination with and without using experts is compared. The result shows the expert weight determination method is an effective approach to improve the accuracy of design concept evaluation.

A fuzzy hybrid decision-making framework for increasing the hospital disaster preparedness: The colombian case

The recent increase in the number of disasters over the world has once again brought to the agenda the question of preparedness of the hospitals, which are the most necessary units of healthcare pillar to resist these disasters. The COVID-19 epidemic disease, which has affected the whole world, has caused a large number of people to die in some countries simply because of the inadequate and incomplete planning and lack of readiness of hospitals. For this reason, determining the disaster preparedness level of hospitals is an important issue that needs to be studied and it is important in terms of disaster damage reduction. In this study, a fuzzy hybrid decision-making framework is proposed to assess hospital disaster preparedness. The framework covers three important decision-making methods. For the first phase, Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) is used to assign relative weights for several disaster preparedness criteria considering uncertainty. Secondly, Intuitionistic Fuzzy Decision Making Trial and Evaluation Laboratory (IF-DEMATEL) is applied to identify interrelations among these criteria and feedback. Finally, via the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, priorities of hospitals regarding disaster readiness are obtained. A case study involving the participation of 10 Colombian tertiary hospitals is carried out to show the applicability of this fuzzy hybrid approach.

Selection of appropriate maintenance strategy using fuzzy VIKOR technique: application in paper industry

Purpose

The industry is relying on the preventive maintenance techniques that can minimize failures and provide industrial plants with effective equipment, but in many companies the maintenance tasks are performed very frequently and not as per plan and do not take into consideration the conditions of the plant and equipments. The failure of each and every component needs to be studied in order to choose the best maintenance strategy. This paper presents a fuzzy VIKOR (Multicriteria Optimization and Compromise Solution) technique which is used in developing a comprehensive approach for maintenance strategy selection in the Deinking plant of the paper industry to choose the appropriate maintenance strategy thereby reducing the unnecessary cost incurred on the maintenance.

Design/methodology/approach

In this paper, the Fuzzy VIKOR based methodology was applied for determining the maintenance criticality index of the deinking plant of the paper industry. The effect of failure of components were evaluated by three maintenance experts on five performance criteria that is chance of failure, chance of non-detection, downtime length, severity, spare part criticality. The components were ranked according to the maintenance criticality index and thereby implementing the appropriate maintenance strategy.

Findings

The Fuzzy VIKOR technique was applied to calculate the ranking of various components of paper industry based on the views and judgment of three maintenance experts. The proposed technique suggested the appropriate maintenance strategy for various components taking into consideration the maintenance criticality index of the components.

Originality/value

The proposed technique will help the maintenance managers to solve a discrete problem with non-commensurable and conflicting criteria. The study will help the industries to reduce the unnecessary maintenance tasks and thereby reduce the maintenance cost. This will help the maintenance practitioners in choosing the best and most effective strategy for the organization with regard to the market and company situation especially in the changing business requirement of Industry 4.0.

Strategies for risk management in adopting Industry 4.0 concept in manufacturing industries

Purpose

This paper aims to concentrate on classifying and analyzing the risks associated with the Industry 4.0 (I4.0) concept in manufacturing industries and developing strategies for managing risks.

Design/methodology/approach

In this research paper, risks categories and their sub-components associated with the I4.0 concept are identified by performing a systematic literature survey of peer-reviewed journal articles and taking inputs from industry experts and academicians. Then, the importance of the identified risks and causal relations among risks are analyzed by using decision-making trial and evaluation laboratory (DEMATEL) method. Finally, the strategies are developed to mitigate the identified risks.

Findings

From the literature survey, 6 risk categories and their 19 sub-components associated with the I4.0 concept are identified. The DEMATEL method resulted in economic risks and technical risks as the top two risk categories in the I4.0 concept. Ecological risks and legal and political risks are relatively low-ranked risk categories.

Research limitations/implications

Causal relations and ranking among risk categories and their sub-components are obtained by analyzing responses received through questionnaires. There are other methods also available for risk analysis, which are beyond this study.

Practical implications

This research paper will help the industrialists to effectively manage the risks involved in adopting I4.0 concept in manufacturing industries by adopting strategies.

Originality/value

This research paper gives an idea about risks associated with the implementation of the I4.0 concept in manufacturing industries. Also, this paper uses the DEMATEL method for ranking the identified risk categories and their sub-components.

Construction of “Space-Sky-Ground” Integrated Collaborative Monitoring Framework for Surface Deformation in Mining Area

Ground deformation measurements in mining areas play a key role in revealing the surface subsidence law, retrieving the subsidence parameters, warning of geological disasters and restoring the surface ecology. With the development of science and technology, there have emerged a great number of monitoring techniques and buildings of diverse protection levels. The diversity of monitoring techniques and the multiplicity of monitoring objects have brought challenges for surface deformation monitoring in the coal industry. Based on the existing deformation monitoring techniques, this paper established a framework of “space-sky-ground” collaborative monitoring system in mining area. We also constructed an AHP-TOPSIS (Analytic Hierarchy Process method- Technique for Order Preference by Similarity to an Ideal Solution) preference model of “space-sky-ground” collaborative monitoring of surface deformation in mining area, and carried out engineering application. Our study shows that the framework of the “space-sky-ground” collaborative monitoring system for surface subsidence in mining areas established in this paper, combined with the AHP-TOPSIS monitoring preference model, which can fully combine the advantages of each monitoring technique, overcome the limitations of a single monitoring technique, comprehensively obtain the surface subsidence data and work out the surface deformation subsidence pattern. This information provides a data and technical support for surface environment management.

Estimating Driver Behavior Measures Related to Traffic Safety by Investigating 2-Dimensional Uncertain Linguistic Data—A Pythagorean Fuzzy Analytic Hierarchy Process Approach

Human behavior has been estimated as a factor too uncertain and complex to investigate road safety issues. By utilizing recent expansions of ordinary fuzzy sets, experts in the field have intended to handle the vagueness of human behavior in sustainable transport systems by using linguistic terms for assessment. Pythagorean Fuzzy sets (PFSs) are considered a superior method that has been developed for multi-criteria decision-making (MCDM), which enables assigning of both membership and non-membership functions in a large domain area. A novel Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP) is performed to assess and prioritize critical driver behavior criteria designed into a hierarchical model based on data gathered from observed driver groups in Budapest city. Accordingly, based on the aggregated weights, the criterion ‘lapses’ is prioritized as the most critical factor connected to road safety. The criterion ‘disobey speed limits’ is found to be the least critical factor, followed by ‘disobey overtaking rules’ as the second least. For a comparative analysis, the case of dependent criteria has been considered. Pythagorean Fuzzy DEMATEL method has been applied to determine dependencies between the criteria. Through the dependencies, a network of criteria has been constructed and the Pythagorean Fuzzy Analytic Network Process (ANP) conducted to interpret the results. Moreover, sensitivity analyses have been carried out to examine its robustness by applying different case scenarios.

Deciding a Multicriteria Decision-Making (MCDM) Method to Prioritize Maintenance Work Orders of Hydroelectric Power Plants

The current global competitive scenario and the increase in complexity and automation of equipment and systems demand better results from maintenance management in organizations. As maintenance resources are limited, prioritizing maintenance activities is essential to allocate them properly and to meet maintenance management objectives. In the face of these challenges, multicriteria decision-making (MCDM) methods are commonly used in organizations to support decision-making. Nevertheless, selecting a suitable MCDM method for maintenance planning can be complicated given the diversity of methods and their strengths and weaknesses. In this context, this paper proposes a novel knowledge-based method for deciding a multicriteria decision-making (MCDM) method to prioritize maintenance work orders of hydroelectric plants. As the main novel contribution, it translates the intrinsic characteristics of the main MCDM methods into questions related to maintenance planning to guide the recommendation of a suitable MCDM method for organizations through a decision tree diagram. This approach was applied to a maintenance case study of a hydroelectric power plant in order to demonstrate its use and contribute to its understanding. These findings contribute to maintenance management in selecting an MCDM method aligned with the context of its maintenance planning for the prioritization of maintenance work orders.

A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters

Hospitals are the first point of contact for people in the face of disasters that interfere with the daily functioning of life and endanger health and social life. All preparations should be made considering the worst possible conditions and the provided service should continue without interruption. In this study, a multi-criteria decision-making model was developed to evaluate disaster preparedness of hospitals. This decision model includes Bayesian best-worst method (BBWM), the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and technique for order preference by similarity to ideal solution (TOPSIS) methods. With the proposed decision model, six main criteria and 34 sub-criteria related to disaster preparedness of hospitals were considered. The criteria and sub-criteria evaluated in pairwise comparison manner by the experts were weighted with BBWM. These weight values and the data obtained from the six Turkish hospitals were combined to provide inputs for VIKOR and TOPSIS. In addition, a comparative study and sensitivity analysis were carried out using weight vectors obtained by different tools. BBWM application results show that the "Personnel" criterion was determined as the most important criterion with an importance value of 26%. This criterion is followed by "Equipment" with 25%, "Transportation" with 14%, "Hospital building" and "Communication" with 12%, and "Flexibility" with 11%. Hospital-2 was determined as the most prepared hospital for disasters as a result of VIKOR application. The VIKOR Q value of this hospital was obtained as 0.000. According to the results of the comparative study, Hospital-2 was determined as the most disaster-ready hospital in all six different scenarios. This hospital is followed by Hospital-4 (Q = 0.5661) and Hospital-5 (Q = 0.7464). The remaining rankings were Hospital-6, Hospital-3 and Hospital-1. The solidity of the results was checked with TOPSIS. Based on TOPSIS application results, Hospital-2 was again found the most-ready hospital. The usage of BBWM in this study enabled the expert group's views to be combined without loss of information and to determine the criteria and sub-criteria weights with less pairwise comparisons in a probabilistic perspective. Via the "Credal ranking", which is the contribution of BBWM to the literature, the interpretation of the hierarchy between each criterion has been performed more precisely.

A Bibliometric Review on Decision Approaches for Clean Energy Systems under Uncertainty

This paper aims to provide a bibliometric review on the diverse decision approaches in uncertain contexts for clean energy system (CES) assessment. A total of 126 publications are analyzed. Previous reviews on CES have discussed several research questions on the decision methods and the applicability of evaluating CES, along with the factors associated with CESs. In the present study, we focus on the bibliometric aspect that attempts to address questions related to the prominence of authors, countries/regions that focus on the current theme, impact of journals, importance of articles in the research community, and so on. The window considered for the study is from 2018 to 2021, with the motive to extend the review process from the preceding works. A review model is presented to address the questions based on the literature evidence. The results infer that CESs are the most viable mode for sustainable development, and the use of decision approaches is apt for the assessment of CESs.

The novel VIKOR methods for generalized Pythagorean fuzzy soft sets and its application to children of early childhood in COVID-19 quarantine

In this work, the new VIKOR methods are established using the generalized Pythagorean fuzzy soft sets (GPFSSs). For GPFSSs, the distance measures such as Hamming, Euclidean, and generalized are given. Further, the basic characteristics of these distance measures are examined. Fuzzy and soft sets are strong instruments for uncertainty. This strongness has been demonstrated by the GPFSS combining Pythagorean fuzzy sets and soft sets and applied to imprecise and ambiguous information. In this context, new remoteness index-based methods have been proposed, which are dissimilar from available VIKOR methods. The displaced and fixed ideals positive and negative Pythagorean fuzzy values (PFV) were defined. Thus, based on this definition, displaced positive ideal remoteness indices, negative ideal remoteness indices, and fixed positive ideal, negative ideal remoteness indices were discussed. Two different weights are used here: weights based on OF preference information and precise weights calculated with the expectation score function. The VIKOR method given here provides a different way from canonical VIKOR methods: rank candidate alternatives and determining a compromise solution based on different preference structures. The processes principles of the newly defined GPFSSs VIKOR methods are given by four algorithms. An example of these algorithms is given with the behavioral development and cognitive development of the children of Early Childhood children in the COVID-19 quarantine.

An integrated approach of PCA and PROMETHEE in spatial assessment of circular economy indicators

In order to ensure environmental sustainability, reducing the consumption of renewable resources, finding adequate substitutes for non-renewable resources, and reducing the generation of waste and pollution are necessities. The concept of circular economy one of the possible and good responses to improve the sustainability of the system, as it places particular emphasis on the reduction, reutilization and recycling of its elements. The paper presents a comparative analysis of the circular economy development in European Union countries based on the dataset encompasses 11 indicators, covering the seven-year period with biennial data. The analysis was performed using the integrated approach of the Principal Component Analysis and PROMETHEE with the aim of creating a composite index as a measure of the development of the circular economy at the national level. The ranking outcomes indicate that during the observed period Germany has the most developed circular economy, followed by the Netherlands, France and Austria. Additionally, the results of the research clearly indicate the positive correlation between the development of circular economies at the national level and the socio-economic development of the country, while progress in the circular economy has no immediate impact on environmental sustainability, but the effects are realized subsequently, with the intensity of the relationship increasing in two-year lag periods.

Multicriteria Decision-Making to Determine the Optimal Energy Management Strategy of Hybrid PV–Diesel Battery-Based Desalination System

This paper identifies the best energy management strategy of hybrid photovoltaic–diesel battery-based water desalination systems in isolated regions using technical, economic and techno–economic criteria. The employed procedures include Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as tools for the solution. Twelve alternatives, containing three–four energy management strategies; four energy management strategies, load following (LF), cycle charging (CC), combined LF–CC, and predictive strategy; and three different sizes of brackish water reverse osmosis (BWRO) water desalination units, BWRO-150, BWRO-250, and BWRO-500, are investigated with capacity of 150, 250, and 500 m3/day, respectively. Eight attributes comprising different technical and economic metrics are considered during the evaluation procedure. HOMER Pro® software is utilized to perform the simulation and optimization. The main findings confirmed that the best energy management strategies are predictive strategies and the reverse osmosis (RO) unit’s optimal size is RO-250. For such an option, the annual operating cost and initial costs are $4590 and $78,435, respectively, whereas the cost of energy is $0.156/kWh. The excess energy and unmet loads are 27,532 kWh and 20.3 kWh, respectively. The breakeven grid extension distance and the amount of CO2 are 6.02 km and 14,289 kg per year, respectively. Compared with CC–RO-150, the amount of CO2 has been sharply decreased by 61.2%.

A Framework for Early Stages of Socially Sustainable Renovation of Multifamily Buildings with Occupants’ Participation

Research shows that in most cases occupants are not actively involved in the design process but only informed about the decisions already made. This paper proposes a framework for the early phases of socially sustainable renovation design of multifamily buildings enabling occupants’ active and timely involvement by defining appropriate mechanisms for participation in a structured manner. It further considers the interdependence of the social, environmental and economic aspects of renovation design and underlines the significance of their simultaneous consideration. The presented research shows the existence of significant heterogeneity, complexity and interdependence of a number of factors that need to be considered in order to adequately conceptualize sustainable building renovations. Finally, the paper discusses future directions for the development of the proposed model.

The Renewable Energy Source Selection by Remoteness Index-Based VIKOR Method for Generalized Intuitionistic Fuzzy Soft Sets

In this paper, we introduce the Euclidean, Hamming, and generalized distance measures for the generalized intuitionistic fuzzy soft sets (GIFSSs). We discuss the properties of the presented distance measures. The numerical example of decision making and pattern recognition is discussed based on the proposed distance measures. We develop a remoteness index-based VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method for GIFSSs. The displaced and fixed ideals intuitionistic fuzzy values (IFVs) are defined. The novel concept of displaced and fixed remoteness indexes for IFVs are discussed. We discuss the methods to obtain the precise and intuitionistic fuzzy (IF) weights. The several displaced and fixed ranking indexes are defined based on the precise and IF weights. The remoteness indexes based VIKOR methods are proposed in the form of four algorithms. In the end, the selection of renewable energy sources problem is solved by using the four remoteness index-based VIKOR methods.

An Integrated Approach of Best-Worst Method (BWM) and Triangular Fuzzy Sets for Evaluating Driver Behavior Factors Related to Road Safety

Driver behavior plays a major role in road safety because it is considered as a significant argument in traffic accident avoidance. Drivers mostly face various risky driving factors which lead to fatal accidents or serious injury. This study aims to evaluate and prioritize the significant driver behavior factors related to road safety. In this regard, we integrated a decision-making model of the Best-Worst Method (BWM) with the triangular fuzzy sets as a solution for optimizing our complex decision-making problem, which is associated with uncertainty and ambiguity. Driving characteristics are different in different driving situations which indicate the ambiguous and complex attitude of individuals, and decision-makers (DMs) need to improve the reliability of the decision. Since the crisp values of factors may be inadequate to model the real-world problem considering the vagueness and the ambiguity, and providing the pairwise comparisons with the requirement of less compared data, the BWM integrated with triangular fuzzy sets is used in the study to evaluate risky driver behavior factors for a designed three-level hierarchical structure. The model results provide the most significant driver behavior factors that influence road safety for each level based on evaluator responses on the Driver Behavior Questionnaire (DBQ). Moreover, the model generates a more consistent decision process by the new consistency ratio of F-BWM. An adaptable application process from the model is also generated for future attempts.

Optimal Spectrum-Hole Detection Scheme for Cooperative CRN Using Dynamic Weighted VIKOR

In the future, the wireless network environment may suffer due to the unavailability of new spectrum bands. Cognitive radio research considers the current spectrum underutilization and provides a better model for the next-generation wireless environment. Since the implementation of the cognitive radio and its policies is a bigger challenge under static spectrum allocation, i.e., current wireless networks policy, many issues are in front of us to accomplish a better cognitive radio wireless environment. One of the major challenges is a secure transmission and efficient free channel selection. In this research, the authors considered an efficient free-channel selection scheme as objective and derived an integrated approach for free-channel selection with techniques, Dynamic weighted-VIKOR.

Evaluation of Influenza Intervention Strategies in Turkey with Fuzzy AHP-VIKOR

In this study, a fuzzy AHP-VIKOR method is presented to help decision makers (DMs), especially physicians, evaluate and rank intervention strategies for influenza. Selecting the best intervention strategy is a sophisticated multiple criteria decision-making (MCDM) problem with potentially competing criteria. Two fuzzy MCDM methods, fuzzy analytic hierarchy process (F-AHP) and fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (F-VIKOR), are integrated to evaluate and rank influenza intervention strategies. In fuzzy AHP-VIKOR, F-AHP is used to determine the fuzzy criteria weights and F-VIKOR is implemented to rank the strategies with respect to the presented criteria. A case study is given where a professor of infectious diseases and clinical microbiology, an internal medicine physician, an ENT physician, a family physician, and a cardiologist in Turkey act as DMs in the process.

Mobile Patient Monitoring Systems from a Benchmarking Aspect: Challenges, Open Issues and Recommended Solutions

This paper presents comprehensive insights into mobile patient monitoring systems (MPMSs) from evaluation and benchmarking aspects on the basis of two critical directions. The current evaluation criteria of MPMSs based on the architectural components of MPMSs and possible solutions are discussed. This review highlights four serious issues, namely, multiple evaluation criteria, criterion importance, unmeasurable criteria and data variation, in MPMS benchmarking. Multicriteria decision-making (MCDM) analysis techniques are proposed as effective solutions to solve these issues from a methodological aspect. This methodological aspect involves a framework for benchmarking MPMSs on the basis of MCDM to rank available MPMSs and select a suitable one. The benchmarking framework is discussed in four steps. Firstly, pre-processing and identification procedures are presented. Secondly, the procedure of weight calculation based on the best-worst method (BWM) is described. Thirdly, the development of a benchmark framework by using the VIKOR method is introduced. Lastly, the proposed framework is validated.

An Extended Picture Fuzzy VIKOR Approach for Sustainable Supplier Management and Its Application in the Beef Industry

Nowadays, sustainable supply chain management (SSCM) has received considerable attention because of strict government requirements and increased pressure from the public. In the SSCM, selecting suitable suppliers plays a significant role in improving the overall sustainability performance of a company. Therefore, this article aims to develop a modified VIKOR (in Serbian: VlseKriterijumska Optimizacija I Kompromisno Resenje) technique for sustainable supplier evaluation and selection, that uses ordered weighted distance operators in the aggregation of picture fuzzy information. Concretely, we first propose the picture fuzzy-ordered weighted standardized distance (PFOWSD) operator and the picture fuzzy Euclidean-ordered weighted standardized distance (PFEOWSD) operator, and extended them by using the hybrid average operator. Then, we develop a sustainable supplier selection approach by combining the picture fuzzy distance operators and the VIKOR method. The new approach can manipulate attitudinal character of the classical VIKOR method, so that a decision maker can take decisions according to his or her preference. Further, by using the PFOWSD operator, one can parametrize the VIKOR method from the maximum to the minimum result. Thus, the information obtained using the new sustainable supplier selection approach is much more complete. Finally, a practical case example in the beef supply chain is given to explain the proposed picture fuzzy-ordered weighted distance (PFOWD)-VIKOR model, and the results are compared with current relevant representative approaches to verify its feasibility and superiority.

Systematic Review of an Automated Multiclass Detection and Classification System for Acute Leukaemia in Terms of Evaluation and Benchmarking, Open Challenges, Issues and Methodological Aspects

This study aims to systematically review prior research on the evaluation and benchmarking of automated acute leukaemia classification tasks. The review depends on three reliable search engines: ScienceDirect, Web of Science and IEEE Xplore. A research taxonomy developed for the review considers a wide perspective for automated detection and classification of acute leukaemia research and reflects the usage trends in the evaluation criteria in this field. The developed taxonomy consists of three main research directions in this domain. The taxonomy involves two phases. The first phase includes all three research directions. The second one demonstrates all the criteria used for evaluating acute leukaemia classification. The final set of studies includes 83 investigations, most of which focused on enhancing the accuracy and performance of detection and classification through proposed methods or systems. Few efforts were made to undertake the evaluation issues. According to the final set of articles, three groups of articles represented the main research directions in this domain: 56 articles highlighted the proposed methods, 22 articles involved proposals for system development and 5 papers centred on evaluation and comparison. The other taxonomy side included 16 main and sub-evaluation and benchmarking criteria. This review highlights three serious issues in the evaluation and benchmarking of multiclass classification of acute leukaemia, namely, conflicting criteria, evaluation criteria and criteria importance. It also determines the weakness of benchmarking tools. To solve these issues, multicriteria decision-making (MCDM) analysis techniques were proposed as effective recommended solutions in the methodological aspect. This methodological aspect involves a proposed decision support system based on MCDM for evaluation and benchmarking to select suitable multiclass classification models for acute leukaemia. The said support system is examined and has three sequential phases. Phase One presents the identification procedure and process for establishing a decision matrix based on a crossover of evaluation criteria and acute leukaemia multiclass classification models. Phase Two describes the decision matrix development for the selection of acute leukaemia classification models based on the integrated Best and worst method (BWM) and VIKOR. Phase Three entails the validation of the proposed system.