Fuzzy Multi-criteria Decision-making Method Research Articles

Intelligent triage method for early diagnosis autism spectrum disorder (ASD) based on integrated fuzzy multi-criteria decision-making methods

BackgroundAutism spectrum disorder (ASD) symptoms and severity levels vary from patient to patient, so treatment and healthcare will vary. However, little attention has been given to developing an autistic triage method for ASD patients concerning four issues: hybrid triage criteria, multi-selection criteria problems, criteria importance, and trade-off based on the inverse relationship between autistic criteria. Therefore, this study aims to develop a new method for triaging ASD patients and classifying them according to their severity of disorder using Fuzzy Multi-Criteria Decision Making (fMCDM) methods. MethodsTwo methodology phases have been conducted: the first phase is to identify and preprocess the ASD dataset, including 988 autistic patients with 42 medical and Sociodemographic criteria. In the second phase, two fMCDM methods were used to develop the triage method. The fuzzy Delphi Method (FDM) is used to select the most influential criteria among the 42 based on thirteen psychologists in the psychological field. Then Fuzzy-Weighted Zero-Inconsistency (FWZIC) is used to assign weights to the important criteria according to four psychologists' opinions. Accordingly, the Processes for Triaging Autism Patients (PTAP) method has been developed for the first time for triaging and classifying patients into three severity levels: minor, moderate, and urgent. ResultsFor the preprocessed phase, 538 out of 988 patients were obtained as a new ASD dataset underwent data cleaning to capture only autism patients. For the second phase, the FDM results have selected 19 out of 42 criteria and can control the bias of psychologists' opinions, FWZIC has assigned the appropriate weights for the 19 criteria, and the PTAP method triages the 538 patients into three severity levels: 36 minor injuries, 432 moderate injuries, and 70 urgent injuries. More complex statistical analyses have been presented using MedCalc statistical software. Three physicians in the psychological field gave their subjective judgements for the diagnosis of 46 random samples of patients. The sensitivity results were 86.67%, 80%, and 90.91%, while the specificity results were 93.55%, 88.46%, and 94.29% for urgent, moderate, and minor levels, respectively. In addition, the accuracy was 91.30% for urgent, 84.78% for moderate, and 93.48% for minor. This assessment led to a deduction that a proposed ASD triage method can be applied with high performance. ConclusionsThe developed triage method can be used for early autism diagnosis application and support clinical treatment utilizing the advantages of fMCDM techniques of multidimensional criteria. Four medical criteria were selected from the psychologists, while Sociodemographic acquired high attention with 15 selected criteria. For the correlation analysis of the 19 used criteria, the ‘Wave’ criterion has the highest correlation with the triage level and obtained 0.4523. On the contrary, the “Pointing with the index finger” criterion has the lowest correlation and obtained −0.0542. Limitations and future works have also been reported in this study. The study confirms the efficacy of the proposed triage method compared with previous studies in five comparative points with 100%.

Assessing the Effect of Building Information Modeling System (BIM) Capabilities on Lean Construction Performance in Construction Projects Using Hybrid Fuzzy Multi-criteria Decision-Making Methods

Assessing the Effect of Building Information Modeling System (BIM) Capabilities on Lean Construction Performance in Construction Projects Using Hybrid Fuzzy Multi-criteria Decision-Making Methods

Maintenance Prioritisation of Irrigation Infrastructure Using a Multi-Criteria Decision-Making Methodology under a Fuzzy Environment

The aging infrastructure and rising demand in the irrigation industry as a result of population growth have increased maintenance works in recent years. The most efficient asset maintenance practice is proactive. However, while a limited budget and an increase in aging infrastructure has made proactive asset maintenance challenging, customers still expect quality service, and contemporary challenges such as climate change and the competitive market further add to the existing pressure on asset owners. In this context, the present work has the primary objective of developing a novel, accurate, efficient and straightforward methodology for measuring assessment criteria weights and using them to prioritise assets for maintenance. For this aim, fuzzy multi-criteria decision-making (MCDM) methods are developed for the optimisation of asset maintenance prioritisation. Using objective and subjective data, the proposed method will be utilised to prioritise six irrigation channels in Northern Victoria, Australia, for maintenance. To verify the efficiency and accuracy of the developed MCDM method, the prioritised channels are validated by comparing against their existing physical condition. Results prove the ability of the proposed method in distinguishing and taking into account the differences between the channels (in terms of their size, physical condition, financial impacts, etc.) in prioritisation for maintenance. This study will also provide suggestions to improve the existing asset maintenance prioritisation methods in practice

Designing a Strategic Human Resource Planning Model: A Case of Export Development Bank of Iran

The current research has compiled a strategic HR planning model in the Export Development Bank of Iran using the fuzzy multicriteria decision-making (MCDM) method. The methodology was applied in terms of its purpose and followed an exploratory and mixed approach, comprising the SWOT matrix and fuzzy MCDM methods. The statistical population in the study consisted of 1620 managers and experts, 313 of whom were determined as the sample size by the stratified sampling with proportional allocation method and Cochran’s formula. Two researcher-made questionnaires with >0.7 reliabilities and validities and five-point Likert scales were used for data collection. Concerning the inferential analysis of the data, the researchers employed the SWARA and fuzzy COPRAS methods to determine the final weights and prioritize the strategies, respectively. The results showed that the strategic HR planning model fitted with the mentioned bank included three main processes, strategy determination, implementation, and evaluation and feedback. Besides, among 19 identified strategies, the aggressive strategy of the necessity for reengineering the processes of recruiting and supplying human forces commensurate with future needs with a terminal value of 0.0662 was prioritized, and it was necessary to alter the current inactive situation toward an aggressive strategy as a strategic step.

Optimal site selection study of wind-photovoltaic-shared energy storage power stations based on GIS and multi-criteria decision making: A two-stage framework

Wind-photovoltaic-shared energy storage system can improve the utilization efficiency of renewable energy resources while reducing the idle rate of energy storage resources. Using the geographic information system (GIS) and the multi-criteria decision-making (MCDM) method, a two-stage evaluation model is first developed for site selection of wind-photovoltaic-shared energy storage projects. In the first stage, infeasible alternatives are ruled out due to veto identification. In the second stage, the fuzzy MCDM method is applied to further merit selection. Firstly, the comprehensive criteria system is built, and evaluation data is collected using probabilistic linguistic term sets (PLTSs) to ensure the comprehensiveness and scientificity of decision. Then, the new score function based on compromise theory are proposed. Thirdly, the criteria weights are calculated using the improved Decision-Making and Trial Evaluation Laboratory (DEMATEL) approach. Finally, the improved gained and lost dominance score (GLDS) method is used to rank alternatives. To test model's feasibility, an empirical study is conducted in Chifeng City. The alternative A1 appears to be extremely prominent in the results. The model's stability and reliability are demonstrated by sensitivity and comparative analysis. This study aids in the layout of wind-photovoltaic-shared energy storage projects and broadens the application scopes of GIS and MCDM method.

Prioritization of R&D Project Evaluation Criteria Using Pythagorean Fuzzy AHP Method

One of the key factors for businesses to ensure their long-term competitiveness is the development of new products/services. In order to do this, they need to carry out R&D projects. However, it is highly risk and uncertainty to identify innovative and high value-added projects from among the many R&D projects in their portfolio. In particular, there are many criteria in the evaluation of projects. The weights of importance given to these criteria at the evaluation stage are very critical. Therefore, the importance of objective evaluation of R&D projects is increasing day by day. In this context, evaluating R&D projects by using fuzzy multi-criteria decision-making methods that eliminate uncertainty and risks will make this process easier. In this study, it is aimed to prioritize the criteria considered in the evaluation of R&D projects. In the study, firstly, the criteria taken into account in the evaluation of R&D projects were determined through the literature and expert opinions. Then, the criteria were prioritized by importance weights by using the Pythagorean fuzzy Analytical Hierarchy Process (AHP) method, which is flexible and powerful in solving the uncertainties that may arise in the evaluation of R&D projects.

Preface

The 2022 2nd International Conference on Energy, Power and Advanced Thermodynamic Systems (EPATS 2022) was successfully held in Nanjing, China in July 22-24, 2022 in the form of online conference. Energy, along with electricity, has become an indispensable part of our life, and they change the way we live. Under such a background, EPATS 2022 focused on the latest innovations and knowledge in energy and power engineering, stimulated new ideas and promoted collaborations in these areas.We had the honor of inviting both Prof. Lim Yun Seng from Universiti Tunku Abdul Rahman, Malaysia and Prof. M.Shahidul Islam from Universiti Malaysia Sarawak, Malaysia to serve as our Conference Chairmen. 120 individuals and enterprises all over the world attended the conference. Divided into three parts, the conference agenda covered keynote speeches, oral presentations, and online Q&A discussion. Firstly, keynote speakers were each allocated 30-45 minutes to hold their speeches. Then in the oral presentations, the excellent papers selected were presented by their authors one by one.During the conference, we were greatly honored to invite four sophisticated keynote speakers to address their speeches. Among them, Assoc. Prof. Sen Guo from North China Electric Power University delivered a thought-provoking speech on the topic: Comprehensive Performance Evaluation of Pumped Storage Power Station in China. In this research, a hybrid novel fuzzy multicriteria decision-making (MCDM) method combining the fuzzy best worst method (BWM) and fuzzy TOPSIS was proposed for the comprehensive performance evaluation of pumped storage power stations in China. Additionally, Prof. Zhenbin Zhang from Shandong University, China presented us his report: Cooperative-Predictive Control of Hybrid Microgrids. This report provided possible control solutions for further MG-based power grid, and presented the latest progress and contribution of his team in this field. Three research aspects were discussed, including predictive control of power converters in the primary layer, cooperative control of multiple distributed generators in the secondary layer as well as cooperative control between the AC and DC heterogeneous sub-grids. The wonderful and dramatic speeches of each keynote speaker had triggered heated discussion. Moreover, every participant praised this conference for disseminating useful and insightful knowledge.We are glad to share with you that we received lots of submissions from the conference and we selected a bunch of high-quality papers and compiled them into the proceedings after rigorously reviewing them. These papers feature but are not limited to the following topics: Energy Storage Technology, Self-Healing of the Power Grid, Power Grid Coordination, Engineering Thermodynamics, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication.On behalf of the conference organizing committee, we would like to express our heartfelt appreciation to all the keynote speakers, peer reviewers, and all the participants. Especially, we would like to acknowledge the Journal of Physics: Conference Series, for the efforts of all the colleagues in publishing this paper volume. We firmly believe that all the attendees have had fruitful discussions and gained valuable knowledge, and will enjoy the opportunity for future collaborations.Committee of EPATS 2022List of Committee member is available in this Pdf.

An ontology-based study on water quality: probabilistic risk assessment of exposure to fluoride and nitrate in Shiraz drinking water, Iran using fuzzy multi-criteria group decision-making models.

World Health Organization reports that 2.2 million people die yearly from insufficient sanitary drinking water. This ontology-based study focused on investigating the chemical quality of drinking water through a new water quality index designed by fuzzy multi-criteria group decision-making methods, merged with GIS, and, secondly, surveying non-carcinogenic risk assessment of fluoride and nitrate using Monte Carlo simulation and sensitivity analysis in Shiraz's water sources. F-, NO3-, NO2-, EC, TDS, alkalinity, TH, SO42-, Cl-, and Na were applied in the WQI. The NO3- mean concentrations were 23.15 and 27.66mg/L in the cold and warm seasons, while the mean concentrations of fluoride were 0.50 and 0.46mg/L during the cold and warm period. The 95th centiles of fluoride's HQs among infants, children, teenagers, and adults were 0.56, 0.7, 0.49, and 0.4, respectively, in the cold season, which was 0.65 and 0.81, respectively, 0.57 and 0.46 for mentioned groups in the warm season. In comparison, the 95th centiles of nitrate's HQs among infants, children, teenagers, and adults were 1.27, 1.59, 1.13, and 0.9, respectively. The HQs were more than 1 for infants, children, and teenagers, so nitrate can have various adverse effects, whereas fluoride does not adversely affect all aging groups in both seasons. Also, nitrate concentration can increase the non-carcinogenic risk, which the IR and ED lead to the HQ increasing. In contrast, BW has a negative effect on risk increasing. Overall, source management of these parameters can significantly reduce the concentration of nitrate and their adverse human health effect.

A Novel MDCM Approach for Sustainable Supplier Selection in Healthcare System in the Era of Logistics 4.0

The COVID-19 pandemic has led to major disruptions in workflows across all industries. All sectors are trying to sustain operations during this extremely difficult time and the healthcare sector is the most important of them. It is unthinkable to stop the operations of the health system because it serves human life. Health institutions must supply the products such as masks, gloves, and ventilators subject to service on time for certain activities to continue indefinitely under all conditions. By adopting modern logistics activities and technologies, healthcare organizations can provide sustainable diagnosis and treatments to patients by automating their various operations. With the COVID-19 pandemic, how to select an appropriate sustainable supplier has become an important task in the era of Logistics 4.0. From this viewpoint, a sustainable supplier selection framework is implemented for a health institution under the effect of the pandemic. To determine the direct effects of the pandemic in the health sector, fuzzy Multi-Criteria Decision-Making (MCDM) methods are utilized in the application. After a thorough review of the literature and interviews with experts, the criteria are organized in a comprehensive hierarchical structure. The fuzzy Best-Worst Method (F-BWM) technique is employed to find the weights for the determined criteria. Consequently, the fuzzy Additive Ratio Assessment Method (F-ARAS) method was applied to rank the alternative suppliers. In addition, with a comprehensive sensitivity analysis, alternative situations are examined against possible breaks in the supply chain. Thus, from the perspective of Logistics 4.0 and sustainability, this study contributes to the literature with an analysis of the health system’s survival in difficult and fragile periods, such as COVID-19. Investigating the importance of SSS can be a road map for the policymakers and the decision-makers is beneficial since the impact of COVID-19 on SSS is studied from the perspective of Logistics 4.0.

Selection of Third-Party Reverse Logistics Service Provider Based on Intuitionistic Fuzzy Multi-Criteria Decision Making

The scientific selection of a third-party reverse logistics service provider (3PRLP) is helpful for enterprises to obtain the expected ecological and economic benefits. Different enterprises have different requirements for 3PRLP selection and, thus, should adopt personalized and simplified evaluation criteria. However, there is a lack of research on criteria screening. Therefore, this paper proposes a criteria screening method based on a rough set for the first time. The 3PRLP selection is a multi-criteria decision making (MCDM) problem in essence, and different criteria can be expressed in different forms. The existing research mostly uses one method for 3PRLP selection, lacking the comprehensive application of various methods. In this paper, various criteria values are transformed into intuitionistic fuzzy numbers (IFNs) for the comparison and combination of various intuitionistic fuzzy MCDM methods. In terms of criteria weighting, a subjective weighting method based on an analytical network process (ANP) is proposed due to the possible correlation between the criteria at the same level. Meanwhile, an objective weighting method based on intuitionistic fuzzy entropy is proposed. The subjective and objective weights are integrated to form the more scientific combination weights. Combining the modeling principles of different intuitionistic fuzzy MCDM methods, the representative methods under each principle are chosen to build a combination evaluation idea that integrates multiple single evaluation models, and the specific evaluation steps are given, including the single evaluation, Kendall compatibility test, combination evaluation, and Spearman consistency test. An illustrative example of 3PRLP selection is provided to verify the feasibility of the methods of criteria screening and weighting and the combination evaluation idea.

Extension of Interval-Valued Fermatean Fuzzy TOPSIS for Evaluating and Benchmarking COVID-19 Vaccines

In order to help curb the spread of the COVID-19 pandemic, this paper develops a multi-attribute decision-making framework for COVID-19 vaccine evaluation based on their major clinical characteristics and efficacy. Firstly, a new multi-criteria Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) modification has been constructed in an interval-valued Fermatean fuzzy (IVFF) environment, improving the shortcomings of traditional TOPSIS. Secondly, a new conceptual framework for static and dynamic evaluation of COVID-19 vaccines has been built. The proposed methodology incorporates a variety of crisp and fuzzy MCDM methods. The analysis of the results of two practical examples shows that the new framework for vaccine comparison is feasible and effective, and finally, some recommendations for enhancement of government anti-COVID-19 strategies are suggested.

OPTIMIZING SERVICE QUALITY MANAGEMENT OF THE BUS RAPID TRANSPORT SYSTEM IN LAGOS USING THE MULTI-CRITERIA DECISION ANALYSIS

Evaluation of Bus Rapid Transportation (BRT) based on service quality criteria and customer satisfaction can never be overemphasized due to its derivative, such as optimizing the performance of the transportation industry. Thus, this study employs the multi-criteria decision-making (MCDM) method for the evaluation of service quality and customer satisfaction of the BRT system in Nigeria using the fuzzy analytical hierarchy process (FAHP) and visekriterijumska optimizacija i kompromisno resenje (VIKOR), which are components of multi-criteria optimization and compromise solution to evaluate notable factors responsible for the user’s perspective. Research design is quantitative and analytical in nature through a survey of experts who are users of BRT services. Samples were drawn through a multi-stage sampling procedure and a total of 402 copies of questionnaires were administered to BRT users based on their experience with the system. Hence, VIKOR and FAHP methods are applied to analyse data retrieved from the field on services quality and performance level. The service quality (SERVQUAL) model (a multi-dimensional research instrument designed to capture consumer expectations and perceptions of service) was modified thereby generating six dimensions and thirty-six service criteria for this research. The FAHP method was employed to determine the weights of the decision criteria because there is a need to measure commuters’ perceptions and expectations based on numerical linguistic variables due to the vague, imprecise and complexity related to the nature of services. The criteria weights and responses of the survey analysis (data) related with the BRT are input for the VIKOR method for ranking. As measuring the perception of service quality based on crispy value can often be misleading, hence, the use of the fuzzy MCDM method can give a more realistic measurement. The result of the multi-criteria decision analysis revealed that pricing quality is the most relevant service quality dimension to users’ satisfaction, followed by the empathy quality dimension. The summary of strength and weakness areas of service quality discovered through the research and its managerial implications with recommendations were related to the appropriate authority in charge of the BRT system for improved performance.

Sludge Valorization Process for Waste-to-Value-Added Products: Process Simulation, Sustainability Assessment, and Fuzzy Multi-Criteria Decision Making

In this paper, a decision-making framework based on process simulation and the fuzzy PROMETHEE II method was proposed to evaluate the performances of the waste management alternatives considering the situation of lacking data and uncertainty. Process simulation and fuzzy multi-criteria decision-making methods were applied to deal with the problem of insufficient data and uncertain information from linguistic descriptions. First, a criteria system covering environmental, economic, technical, and social aspects was established for sustainability evaluation. Then, sustainability assessment was conducted based on the results of process simulation. The fuzzy best–worst method was applied to obtain the fuzzy weights for the criteria based on the preferences of stakeholders, and the fuzzy PROMETHEE II approach was presented to generate the ranking for all the alternatives. A case study for the prioritization of sludge-to-energy technologies was carried out to demonstrate the feasibility of the proposed framework. Sensitivity analysis and uncertainty analysis were also conducted to verify the stability and robustness of the model. Results indicate the effectiveness of the proposed model on providing reference for the waste-to-energy alternatives ranking and giving constructive suggestions for the industry and future research directions. The constructed model can not only provide useful references for decision-makers but also can inspire researchers to investigate biomass management technologies in a similar framework, and the application may even extend to other fields.

Transformation and risk assessment of the East Kolkata Wetlands (India) using fuzzy MCDM method and geospatial technology

The East Kolkata Wetlands (EKW) is located on the eastern periphery of the city of Kolkata and extends up to the Bidyadhari-Matla River confluence. It is a Ramsar Site and acts as an absorber basin for a large number of contaminants drained from Kolkata. Agricultural lands, sewage-fed fisheries, garbage dumping fields, horticulture, and built-up areas are included in this protected area, that covers approximately 125 km2. It reveals that climate change reduces the variety of wetland ecosystem services and increases socio-economic vulnerability and economic stress. The human encroachment, reclamation of land for agriculture, aquaculture, and urban expansion in and around Kolkata has recently adversely threatened the EKW. The remotely sensed data, socio-economic data, and responses of inhabitants have been used to analyse the EKW’s risk and vulnerability. We employed geospatial analysis by using the Multi-Criteria Decision Making (MCDM) method using nine risk factors. An in-depth analysis of the EKW using geospatial techniques and the Fuzzy Analytic Hierarchy Process (FAHP) helped to understand the EKW transformations through vulnerability and risk analysis. The results show that the transformation of the wetland to aquaculture, eutrophication and pollution, road proximity, waste dumping, population density, and growth are the main factors for the deteriorating health, quality, and environment of the EKW. It also reveals that quantitative and qualitative evaluations of ecosystem services, wetland degradation, transformation, and cause-effect rapport should be periodically assessed using scientific methods like FAHP, RS, GIS to formulate resilient, integrated plans and strategy for the sustainable management of the EKW.

A Two-Step Fuzzy MCDM Method for Implementation of Sustainable Precision Manufacturing: Evidence from China

Despite that products of precision manufacturing are widely used in many fields involving the national economy, precision manufacturing processes are more unfriendly to the environment, resources and social development than general manufacturing. Hence, the implementation of sustainable precision manufacturing (SPM) is of great strategic significance. There is no literature identifying and ranking the drivers of implementation of SPM and the impact on sustainability owing to the application of advanced manufacturing technologies in SPM has not been explored. To resolve these problems, drivers of SPM are identified based on combined support of prior studies and six groups of experts consisting of 71 individuals from six precision manufacturing enterprises. The drivers are calculated and ranked by a two-step fuzzy MCDM method which integrated the fuzzy AHP (fuzzy analytic hierarchy process) and fuzzy TOPSIS (fuzzy technique for order of preference by similarity to ideal solution) algorithms. The evaluation of drivers is based on the basic principles of sustainable development (environmental criterion, social criterion and economic criterion). The paper concludes that technological innovation, government support and current legislation are the most critical drivers during SPM implementation. Additionally, the result of sensitivity verification of the proposed method conducted proves the robustness and correctness of the algorithm and results.

Review on fuzzy multi-criteria decision-making methods in medical diagnosis

In a real-world computing environment, the information is not complete, precise, and certain, making it very difficult to derive an actual decision. Uncertainty is a factor that makes the decision-making process more difficult in medical diagnosis. Everyone is different from the other at the physical level as well as mental level, symptoms of a disease expressed by patients are linguistic in nature and vary from person to person. That is why Decision making in medical diagnosis is becoming a vast research field in medical science. In medical diagnosis, generally, uncertainty (vagueness or imprecision) arises due to patients’ vague linguistic expression of their problems to medical experts. The field of medicine and decision-making are the most fruitful and interesting areas of applications of fuzzy set theory. In the present paper, we study the importance of different fuzzy sets and fuzzy multi-criteria decision-making methods in the field of medical diagnosis.

Interval-valued Pythagorean fuzzy multi-criteria decision-making method based on the set pair analysis theory and Choquet integral

This paper proposes a novel fuzzy multi-criteria decision-making method based on an improved score function of connection numbers and Choquet integral under interval-valued Pythagorean fuzzy environment. To do so, we first introduce a method to convert interval-valued Pythagorean fuzzy numbers into connection numbers based on the set pair analysis theory. Then an improved score function of connection numbers is proposed to make the ranking order of connection numbers more in line with reality in multi-criteria decision-making process. In addition, some properties of the proposed score function of connection numbers and some examples have been given to illustrate the advantages of conversion method proposed in the paper. Then, considering interactions among different criteria, we propose a fuzzy multi-criteria decision-making approach based on set pair analysis and Choquet integral under interval-valued Pythagorean fuzzy environment. Finally, a case of online learning satisfaction survey and a brief comparative analysis with other existing approaches are studied to show that the proposed method is simple,convenient and easy to implement. Comparing with previous studies, the method in this paper, from a new perspective, effectively deals with multi-criteria decision-making problems that the alternatives cannot be reasonably ranked in the decision-making process under interval-valued Pythagorean fuzzy environment.

An intuitionistic fuzzy decision support system for COVID-19 lockdown relaxation protocols in India

In January 2020, the World Health Organization (WHO) identified a world-threatening virus, SARS-CoV-2. To diminish the virus spread rate, India implemented a six-month-long lockdown. During this period, the Indian government lifted certain restrictions. Therefore, this study investigates the efficacy of India’s lockdown relaxation protocols using fuzzy decision-making. The decision-making trial and evaluation laboratory (DEMATEL) is one of the fuzzy MCDM methods. When it is associated with intuitionistic fuzzy circumstances, it is known as the intuitionistic fuzzy DEMATEL (IF-DEMATEL) method. Moreover, converting intuitionistic fuzzy into a crisp score (CIFCS) algorithm is an aggregation technique utilized for the intuitionistic fuzzy set. By using IF-DEMATEL and CIFCS, the most efficient lockdown relaxation protocols for COVID-19 are determined. It also provides the cause and effect relationship of the lockdown relaxation protocols. Additionally, the comparative study is carried out through various DEMATEL methods to see the effectiveness of the result. The findings would be helpful to the government’s decision-making process in the fight against the pandemic.

A risk allocation model among the elements of freeway projects in public-private partnership (PPP) method using integrated fuzzy multi-criteria decision-making techniques

ABSTRACT In the present study, an appropriate risk assessment and allocation model was developed between the various elements of PPP based infrastructure projects. For this purpose, after a review of the research literature and identification of the most important risks, with a case study on PPP-based freeway projects in Iran, a systematic model for risk assessment using fuzzy MCDM methods including FAHP has developed in order to critical risk assessment (Objective 1), FTOPSIS Identification of Common Risks in PPP Transportation Projects (Objective 2) and FDEMATEL for Allocation and Impact of Risk Between Different Project Elements (Objective 3). The results of risk analysis by FAHP method showed that economic and financing, construction and operational risks have the greatest impact, respectively. In addition, the results of FTOPSIS method showed that projects Isfahan-Shiraz Freeway, Salafchegan-Arak Freeway and Khorramabad-Arak Freeway, respectively, were more affected by risks. Finally, the results of FDEMATEL analysis show the degree of interaction and impact strength of risks for each risk and from the perspective of each project manager, which indicates a significant relationship between different risks. The results of this research can be used as a management model in the process of evaluation and risk management of PPP projects.

Evaluation of Different Plagiarism Detection Methods: A Fuzzy MCDM Perspective

Due to the overall widespread accessibility of electronic materials available on the internet, the availability and usage of computers in education have resulted in a growth in the incidence of plagiarism among students. A growing number of individuals at colleges around the globe appear to be presenting plagiarised papers to their professors for credit, while no specific details are collected of how much was plagiarised previously or how much is plagiarised currently. Supervisors, who are overburdened with huge responsibility, desire a simple way—similar to a litmus test—to rapidly reform plagiarized papers so that they may focus their work on the remaining students. Plagiarism-checking software programs are useful for detecting plagiarism in examinations, projects, publications, and academic research. A number of the latest research findings dedicated to evaluating and comparing plagiarism-checking methods have demonstrated that these have restrictions in identifying the complicated structures of plagiarism, such as extensive paraphrasing as well as the utilization of technical manipulations, such as substituting original text with similar text from foreign alphanumeric characters. Selecting the best reliable and efficient plagiarism-detection method is a challenging task with so many options available nowadays. This paper evaluates the different academic plagiarism-detection methods using the fuzzy MCDM (multi-criteria decision-making) method and provides recommendations for the development of efficient plagiarism-detection systems. A hierarchy of evaluation is discussed, as well as an examination of the most promising plagiarism-detection methods that have the opportunity to resolve the constraints of current state-of-the-art tools. As a result, the study serves as a “blueprint” for constructing the next generation of plagiarism-checking tools.