Fuzzy VIKOR method: A case study of the hospital service evaluation in Taiwan

Multi-attribute decision making based on VIKOR with probabilistic linguistic term sets: An application to the risk evaluation of foreign direct investment

The multiple global environments have triggered changes in the international environment, leading to a sharp decline of foreign direct investment (FDI) compared to pre-pandemic level. To evaluate the investment risk of FDI and make optimal investment decision becomes the most important issue for investors. This paper focuses on the evaluation of investment risk for FDI. First, an index system for risk evaluation of FDI is constructed. Then, we introduce the probabilistic linguistic entropy and cross entropy measures, based on which, a programming model is developed to identify the objective attribute weights. A composite weight derivation method, which takes both the objective attribute weights and the subjective attribute weights into account, is further introduced. In view of attributes' uncertainty and fuzziness and the conflicting characteristics of some attributes, the VIKOR (the Serbian name: VlseKriterijumska Optimizacija I Kompromisno Resenje, means multi-criteria optimization and compromise solution) method is used to evaluate the risk of FDI under the probabilistic linguistic environment. Furthermore, a case study is presented to illustrate the proposed method. The comparative analysis and some further discussions verify the validity of the proposed method for the FDI risk evaluation.

A fuzzy rough copula Bayesian network model for solving complex hospital service quality assessment

Healthcare tends to be one of the most complicated sectors, and hospitals exist at the core of healthcare activities. One of the most significant elements in hospitals is service quality level. Moreover, the dependency between factors, dynamic features, as well as objective and subjective uncertainties involved endure challenges to modern decision-making problems. Thus, in this paper, a decision-making approach is developed for hospital service quality assessment, using a Bayesian copula network based on a fuzzy rough set within neighborhood operators as a basis of that to deal with dynamic features as well as objective uncertainties. In the copula Bayesian network model, the Bayesian Network is utilized to illustrate the interrelationships between different factors graphically, while Copula is engaged in obtaining the joint probability distribution. Fuzzy rough set theory within neighborhood operators is employed for the subjective treatment of evidence from decision makers. The efficiency and practicality of the designed method are validated by an analysis of real hospital service quality in Iran. A novel framework for ranking a group of alternatives with consideration of different criteria is proposed by the combination of the Copula Bayesian Network and the extended fuzzy rough set technique. The subjective uncertainty of decision makers' opinions is dealt with in a novel extension of fuzzy Rough set theory. The results highlighted that the proposed method has merits in reducing uncertainty and assessing the dependency between factors of complicated decision-making problems.

Selection of outsourcing logistics providers in the context of low-carbon strategies

As more attention is given to climate change and sustainable development in China, enterprises start to care about carbon emissions related to their supply chains. One important issue faced by an enterprise is to select a logistics provider who can provide a high-quality service with low carbon levels. To solve this issue, this paper proposes a selection criterion from the perspective of low carbon levels based on previous studies. The selection criterion consists of comprehensive strength, financial status, market competitiveness, development potential and low carbon level. Next, this paper applies a combined method of information entropy and grey correlation vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) model to evaluate the proposed selection criterion. Subsequently, this paper took company S and its four logistics providers as a case study to check the applicability of our proposed selection method and to illustrate how to use it. Sensitivity analysis and comparative analysis are also conducted. Related managerial insights are also proposed based on the evaluation results. One finding of this paper is to establish a decision-making framework to evaluate logistics suppliers under the new background of 'emission peak and carbon neutrality'.

Fuzzy incomplete linguistic preference relations

The effectiveness of preference relations in modeling decision-making processes makes it one of the most common representations of information use for solving decision-making problems. This research presents the fuzzy incomplete linguistic preference relations (Fuzzy InLinPreRa) approach as evaluated by decision-makers dealing with increasing complexity and uncertain economics, as well as social and managerial problems. By using Fuzzy InLinPreRa, the consistency measurements of decision-makers' evaluations will provide more accurate and reasonable solutions, allowing decision-makers to consider the objective weights of both the criteria and experts. An empirical example of the measurement of brand personality is included herein to demonstrate the feasibility of this method.

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.

Evaluation of digital economy development level based on multi-attribute decision theory

The maturity and commercialization of emerging digital technologies represented by artificial intelligence, cloud computing, block chain and virtual reality are giving birth to a new and higher economic form, that is, digital economy. Digital economy is different from the traditional industrial economy. It is clean, efficient, green and recyclable. It represents and promotes the future direction of global economic development, especially in the context of the sudden COVID-19 pandemic as a continuing disaster. Therefore, it is essential to establish the comprehensive evaluation model of digital economy development scientifically and reasonably. In this paper, first on the basis of literature analysis, the relevant indicators of digital economy development are collected manually and then screened by the grey dynamic clustering and rough set reduction theory. The evaluation index system of digital economy development is constructed from four dimensions: digital innovation impetus support, digital infrastructure construction support, national economic environment and digital policy guarantee, digital integration and application. Next the subjective weight and objective weight are calculated by the group FAHP method, entropy method and improved CRITIC method, and the combined weight is integrated with the thought of maximum variance. The grey correlation analysis and improved VIKOR model are combined to systematically evaluate the digital economy development level of 31 provinces and cities in China from 2013 to 2019. The results of empirical analysis show that the overall development of China's digital economy shows a trend of superposition and rise, and the development of digital economy in the four major economic zones is unbalanced. Finally, we put forward targeted opinions on the construction of China's provincial digital economy.

Occupational health and safety risk assessment using a fuzzy multi-criteria approach in a hospital in Chennai, India

Objectives. Hospitals provide direct and indirect employment benefits to medical professionals. Accidents in hospitals often lead to disastrous consequences such as fatalities, property damage and economic losses. It is, therefore, imperative to have an occupational health and safety (OHS) policy that aims to reduce work-related accidents to acceptable levels. This study aims to investigate health risks to staff from various hazards and suggest control measures to prevent recurrence of accidents. Methods. A two-stage fuzzy multi-criteria decision-making (MCDM) approach incorporating the fuzzy analytical hierarchical process (FAHP) and fuzzy technique for order preference for similarity to ideal solution (TOPSIS) was applied to assess the hazards in a leading multi-speciality hospital in Chennai. Results. The top three hazards identified in the workplace were electrical hazards, faulty medical equipment, and ventilation and air conditioning hazards. Subsequently, control measures were suggested to reduce the recurrence of hazards. Finally, a survey of hospital accidents occurring in India between 2010 and 2020 was conducted and compared with the results of this study. Conclusions. The survey findings show similarity to the hazard rankings obtained in this work, thus validating the methodology used for the assessment of hazards in hospitals. Electrical hazards and faulty medical equipment should be monitored.

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.

BIM for the Realization of Sustainable Digital Models in a University-Business Collaborative Learning Environment: Assessment of Use and Students’ Perception

This paper develops an assessment of an academic implementation of building information modeling (BIM) carried out in an expert project subject of a School of Industrial Engineering. The objectives were for the students discover sustainable industrial during the design process and the students understand and participate in a real process of the implementation of industrial projects through real collaboration between academic and business contexts. The outcomes of this academic initiative were evaluated using academic results as well as students’ perceptions. Academic results were analyzed using the FUZZY VIKOR method. An analysis of variance (ANOVA) was performed to determine whether the use of BIM, the proposed university-enterprise environment and the sustainability proposal rate of the students’ projects had statistically significant effects on the results. Students´ perception evaluation was based on a Likert survey with five levels, and the results were interpreted using fuzzy k-means clustering and classification tree analysis. The results show that 77.8% of students consider that for learning, it is more effective to carry out a project related to an existing company, with the realization of the project with BIM methodology being of great value. The sustainability aspects were applied more easily thanks to the proposed methodology, and they were positively valued by the company.

An enhanced VIKOR method for multi-criteria group decision-making with complex Fermatean fuzzy sets

This paper aims to propose a new decision-making approach retaining the fascinating traits of the conventional VIKOR method in the context of the enrich multidimensional complex Fermatean fuzzy $ N $-soft set. The VIKOR technique is contemplated as the most reliable decision-making approach among others which employs a strategy to identify the compromise solution with advantageous distance from the positive ideal solution possesses maximum majority utility and minimum individual regret. At the same time, the paramount characteristic of the complex Fermatean fuzzy $ N $-soft set considers the proclivity to capture two-dimensional uncertain and imprecise information along with the multi-valued parameters. This article expands the literature to handle the multi-attribute group decision-making strategy by introducing a technique, namely, the complex Fermatean fuzzy $ N $-soft VIKOR method that amalgamates the unconventional traits of complex Fermatean fuzzy $ N $-soft with the capability of the VIKOR method. The proposed technique permits the assignment of the $ N $-soft grades to the decision-makers, alternatives, and attributes based on their performances. Firstly, we unify these individual opinions of all decision-makers about the alternatives by employing the complex Fermatean fuzzy $ N $-soft weighted average operator. After that, all entities of the aggregated decision matrix are converted into crisp data by utilizing the score function. Furthermore, we calculate the ranking measures of the group utility and the individual regret by assigning the weight of strategy belongs to the interval $ [0, 1]. $ To find the compromise solution, we arrange the ranking measures in ascending order, and the alternative that possesses the conditions of compromise solution is selected. We demonstrate the presented multi-attribute group decision-making technique by selecting the best location for a nuclear power plant. We conduct the comparative analysis of the presented technique with Fermatean fuzzy TOPSIS to endorse the veracity and accuracy of our method. Finally, we explain the merits and limitations of our strategy and give some concluding remarks.

Healthcare performance management using integrated FUCOM-MARCOS approach: The case of India

AIMS

The goal of this research is to propose a simpler and more efficient model for evaluating healthcare establishments (HCEs). With this motivation, this study aims to discover key performance indicators (KPIs) that affect HCE performance, present a ranking model for KPIs in Indian HCEs, and evaluate Indian HCEs using the identified and prioritised KPIs.

MATERIAL AND METHODS

Through extensive literature review and expert opinions, this research identifies the various KPIs in HCEs, classifies them into six main categories, and prioritises them using the full consistency method (FUCOM). Further, well-known HCEs across northern India were evaluated and ranked using Measurement Alternatives and Ranking according to Compromise Solution.

RESULTS

The 'technology adoption related indicators' is found as the most important main KPIs, whereas 'adequate number of hospital beds and bathrooms (IE5)' as the most dominating sub-category KPIs. Also, amongst the 20 evaluated Indian HCEs 'healthcare establishment-1 (HCE1)' was found to be the best performing HCE while 'healthcare establishment-12 (HCE12)' was found to be the worst-performing HCE. The stability and consistency of the results are ascertained by performing sensitivity analysis and comparing the results with other existing methodologies.

CONCLUSION

The findings of this study are quite important for HCEs management to fully comprehend the key areas to improve upon so that managers can improve medical standards in a targeted manner. The developed prioritisation model and methodology shown in this paper will help and motivate managers and intellectuals of HCEs to evaluate and improve the HCE's performance.

A Multi-Criteria Framework to Evaluate the Sustainability of Renewable Energy: A 2-Tuple Linguistic Grey Relation Model from the Perspective of the Prospect Theory

The unique resources and environmental advantages of renewable energy make it an essential component of energy strategies and a meaningful way to achieve “carbon neutrality”. However, due to limitations relating to ecological factors and geographical locations, renewable energy power generation faces many problems, including instability, resulting in unsustainable development. Few studies have been conducted on the sustainability of renewable energy. Therefore, a multi-criteria decision-making (MCDM) framework for evaluating renewable energy sustainability is put forward. Based on a 2-tuple linguistic grey relation model and the prospect theory, the MCDM framework can comprehensively analyze the factors that may influence renewable energy sustainability in terms of resources, the environment, society, technology, and the economy. The combination of the 2-tuple linguistic model and the prospect theory can improve the objectivity of decision making. Taking China as the research object, this study finds that the profit–loss ratios for the four alternatives considered are {0.969,0.432,0.395,0.369} for solar photovoltaic power, wind power, hydropower, and biomass power, respectively, ranked from best to worst. Based on the sensitivity analysis, the MCDM framework can change its parameters based on the relevant psychological characteristics and then establish a suitable system for decision making. The MCDM framework proposed in this study can provide investors with decision-making references and help governmental agencies formulate renewable energy policies.

A facilitating framework for a developing country to adopt smart waste management in the context of circular economy

To achieve higher standards of sustainability, the waste management sector now requires the incorporation of circular economy (CE) principles. However, an easy transition toward the particular goal would require the use of smart waste technologies. To achieve the aforementioned goal, this study aims to provide a facilitating framework for the adoption of smart waste management in the context of CE for Pakistan. To help Pakistan transition toward the new paradigm, a total of 16 critical facilitators are evaluated based on five distinctive criteria using a novel fuzzy hybrid multi-criteria decision-making (MCDM) approach. The hybrid MCDM approach includes fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) for allocating weights to the determined criteria; whereas, the fuzzy VIšekriterijumsko kompromisno rangiranje (VIKOR) approach is used to rank the critical facilitators adopted from the secondary literature. The fuzzy approach in both cases is to deal with any kind of uncertainty during the data collection process. Based on the achieved results, the study suggests that before the application of smart waste technologies in the country, Pakistan should first focus on devising regulations that effectively address the mismanagement of waste produced in the country. Also, the industries in the country need to become more responsible and should adopt environmental management systems that foster waste minimization. Lastly, the country in the third phase should focus on the wide application of digitalization both in the streams of ICT and IoT, for collecting, sharing, and receiving waste data. The study further provides policy recommendations to the respective stakeholders that will help the country achieve zero-waste CE.

Design and Definition of a New Decision Support System Aimed to the Hierarchization of Patients Candidate to Be Admitted to Intensive Care Units

The triage processes prior to the assignation of healthcare resources in hospitals are some of the decision-making processes that more severely affect patients. This effect gets even worse in health emergency situations and intensive care units (ICUs). Aiming to facilitate the decision-making process, in this work the use of vague fuzzy numbers is proposed, aiming to define a multi-attribute patient hierarchization method to be used in emergency situations at hospital ICUs. The incorporation of fuzzy models allows for modelling the vagueness and uncertainty associated with decision criteria evaluation, with which more efficient support is provided to the decision-making process. After defining the methodology, the effectiveness of this new system for patient hierarchization is shown in a case study. As a consequence of that, it is proved that the integration of decision-support systems into healthcare environments results to be efficient and productive, suggesting that if a part of the decision process is supported by these systems, then the errors associated with wrong interpretations and/or diagnoses might be reduced.

An integrated approach for service quality evaluation of online health communities based on q-rung orthopair fuzzy linguistic aggregation operators

Online health communities (OHCs) have emerged as a significant platform for people communicating health information and self-healthcare management. In recent, the researches focusing on its performance measurement and the service quality evaluation have drawn intensive attention. Although some qualitative methods have made evaluation and analyses for the OHCs performance, the studies based on fuzzy multi-attribute decision making theory are rarely developed in the service quality evaluation of OHCs. In view of the complexity and uncertainty of evaluation mission, this paper develops an integrated evaluation approach of the OHC service quality based on the q-rung orthopair fuzzy linguistic aggregation operators. Firstly, we propose the cross-entropy of q-rung orthopair fuzzy numbers, which is applied in solving the optimal weight of indicators by a linear programming model. Next, the q-rung orthopair fuzzy linguistic power average (q-ROFLPA) and q-rung orthopair fuzzy linguistic partitioned dual Maclaurin symmetric mean (q-ROFLPDMSM) operators are developed for aggregating the assessment information and ranking the OHCs. Based on the proposed aggregation operators, the evaluation indicator system and an evaluation framework are constructed to accomplish the service quality evaluation of OHCs. Finally, a practical evaluation case of OHCs is provided to demonstrate the reliability and advantages of the proposed approach.

The operational properties of linguistic interval valued q-Rung orthopair fuzzy information and its VIKOR model for multi-attribute group decision making

As a generalization of linguistic q-rung orthopair fuzzy set (Lq-ROFS), linguistic interval valued q-Rung orthopair fuzzy set (LIVq-ROFS) is a new concept to deal with complex and uncertain decision making problems which Lq-ROFS cannot handle. Due to the lack of information in decision making process, decision makers mostly prefer to give their preferences in interval form rather than a crisp number. In this situations, LIVq-ROFS appears up as a useful tool. In this work, we define operational laws of LIVq-ROFS and prove some properties. Furthermore, we propose the conception of the LIVq-ROF weighted averaging operator and give its formula by mathematical induction. To compare two or more linguistic interval valued q-Rung orthopair fuzzy numbers (LIVq-ROFNs), the improved form of score function is also given. Considering the powerfulness of LIVq-ROFSs handling ambiguity and complex uncertainty in practical problems, the key innovation of this paper is to develop the linguistic interval-valued q-rung orthopair fuzzy VIKOR model that is significantly different from the existing VIKOR methodology. The computing steps of this newly created model are briefly presented. Finally, the effectiveness of model is verified by an example and through comparative analysis, the superiority of VIKOR method is further illustrated.

A new computer-based index for swimming pools' environmental health assessment in big data environment by consensus-based fuzzy group decision-making models

Swimming pools are popularly used for sport and recreational purposes worldwide. These places influence swimmers' health as they are considered public places. This study attempted to introduce a process mining framework which analyzes the environmental health status in swimming pools. In this context, a new numerical index namely Swimming Pool Environmental Health Index (SPEHI) was developed through which, big data extracted from checklists of environmental health inspection of swimming pools were analyzed in fuzzy environment. The methodology comprises MCDM (Multi- Criteria Decision-Making) approach including fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and fuzzy OWA (Ordered Weighting Average). The performance of this index was evaluated through an applied example on 12 swimming pools in Shiraz, Iran that was run for a three-year sequence from 2015 to 2017. Among 30 evaluation criteria used in this index, the greatest (0.61) and lowest (0.35) group weights were dedicated to "Residual chlorine biological water quality" and "existence of drinking water facilities", respectively. For the study area, SPEHI showed a wide range of environmental health conditions between 37.8 (Relatively good) to 98.19 (Excellent). The extended index could shrink swimming pool's big data to concise values which are interpretable for health experts and managers of sport sector. It helps figuring out the trends of hygiene conditions in a swimming pool over the time and easy access to compare a city's swimming pools as well. The methodology is flexible in structure and thus, it could be applied for other sporting places.

Implementing MCDM Techniques for Ranking Renewable Energy Projects under Fuzzy Environment: A Case Study

Energy requirements have increased dramatically due to industrialization, economic, and population growth. To meet this demand, and solve its challenges, such as climate change, renewable energies do play an important role. This research work aims at selecting the best renewable energy projects using a hybrid decision-making framework from environmental, economic, technical, and social aspects at a sub-national level. In this regard, a new hybrid fuzzy multi-criteria decision-making model is deployed in which Vise Kriterijumska Optimizacija I Kompromisno Resenje, distance from average solution, and additive ratio assessment methods are used. In addition, for the weighing of criteria, Fuzzy Shannon’s entropy is used. Furthermore, the North Khorasan province is nominated as a sub-national study area. The results show that among 30 sub-criteria, social acceptance, net-presented cost, and noise were the top three with weights of 0.1105, 0.1003, and 0.0988, respectively. Solar energy projects also accomplished high ranks with an overall score of roughly 0.22. After that, small hydropower got second place with a score of 0.187. Moreover, the ranking of cities indicates that Jajarm was the most suitable location for implementing renewable energy development with a score of 0.14. Finally, sensitivity analysis was carried out to show that the mathematical model possessed good robustness.

Exploring and measure the performance of the Indian petroleum supply chain

Purpose

This research identifies the supply chain performance indices and designs an evaluation framework to assess and compare the Indian petroleum supply chain performance. We presented a case study of three Indian petroleum companies. For this purpose, we identified fifteen performance criteria extracted from previous literature and expert inputs and classified them into four groups.

Design/methodology/approach

A fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) method is employed for evaluating the performance of the Indian petroleum supply chain.

Findings

The design and evaluation framework suggests that the top three performance measurement criteria, the purity of the products, compliance with environmental laws, and new technology adoption. The result findings also indicate that company C contributes to a maximum satisfaction level of 77%. Simultaneously, companies A and B hold satisfaction levels of 72% and 67%.

Practical implications

The managers should ensure that environmental standards, new technology adoption, and quality are significant concerns in the petroleum supply chain. The managers should follow national and international policies to preserve the environment and ensure safety in operational activities.

Originality/value

This paper makes two contributions in the domain of performance measurement of the petroleum supply chain. First, it identifies the prominent supply chain performance indices. Second, it proposes a model to assess and compare the performance of Indian petroleum companies.

A Hybrid Approach of VIKOR and Bi-Objective Decision Model for Emergency Shelter Location–Allocation to Respond to Earthquakes

Earthquakes have catastrophic effects on the affected population, especially in undeveloped countries or regions. Minimizing the impact and consequences of earthquakes involves many decisions and disaster relief operations that should be optimized. A critical disaster management problem is to construct shelters with reasonable capacity in the right locations, allocate evacuees, and provide relief materials to them within a reasonable period. This study proposes a bi-objective hierarchical model with two stages, namely, the temporary shelter stage and the short-term shelter stage. The proposed objectives at different stages are to minimize the evacuation time, maximize the suitability based on qualitative factors, and minimize the number of sites while considering the demand, capacity, utilization, and budget constraints. The performance evaluation of the emergency shelter was carried out by fuzzy-VIKOR, and the most ideal location of the shelter was determined through multiple standards. Emergency management organizations can benefit from the collective expertise of multiple decision-makers because the proposed method uses their knowledge to automate the location and allocation process of shelters. In the case of Chengdu, Sichuan Province, China, the results of using this hybrid approach provide the government with a range of options. This method can realize the trade-off between efficiency and cost in the emergency shelter location and material distribution, and realize reliable solutions in disaster emergencies.

A Compromised Decision-Making Approach to Third-Party Logistics Selection in Sustainable Supply Chain Using Fuzzy AHP and Fuzzy VIKOR Methods

With the effects of the COVID-19 pandemic, the e-commerce trend is driving faster, significantly impacting supply chains around the world. Thus, the importance of logistics and supply chain functions has been amplified in almost every business that ships physical goods. In Vietnam, the logistics service sector has seen rapid expansion. Since more and more businesses are seeking third-party logistics (3PL) providers to outsource the logistics functions, this article aims to offer decision-makers an integrated and consistent model for evaluating and selecting the most efficient 3PLs. To this end, the authors exploit a hybrid multi-criteria method which is fuzzy analytic hierarchy process (FAHP) and fuzzy vlsekriterijumska optimizacija i kompromisno resenje (FVIKOR) while examining the most influential and conflicting criteria regarding economic, service level, environmental, social, and risk aspects. Fuzzy information in the natural decision-making process is considered, linguistic variables are used to mitigate the uncertain levels in the criteria weights. First, FAHP (the weighting method) is adopted to evaluate and calculate each criterion’s relative significant fuzzy weight. FVIKOR (the compromised ranking method) is then used to rank the alternatives. The combination of FAHP and FVIKOR methods provides more accurate ranking results. As a result, reliability and delivery time, voice of customer, logistics cost, network management, and quality of service are the most impactful factors to the logistics outsourcing problem. Eventually, the optimized 3PLs were determined that fully meet the criteria of sustainable development. The developed integrated model offers the complete and robust 3PLs evaluation and selection process and can also be a powerful decision support tool for other industries.

Evaluation of Rhodotorula spp. contamination in hospital environments

Microbiological monitoring of air and surfaces is a valuable tool for assessing the level of environmental contamination by bacteria and fungi in hospitals, especially in high-risk wards. The presence of these microorganisms requires strict control in view of their role as opportunistic pathogens. As regard yeasts, Candida albicans is one of the main opportunistic pathogens. However, in recent years, many other "non-Albicans" species have been identified that are implicated in the onset of both localised infections in immunocompetent patients and systemic infections in immunocompromised patients. The aim of the work was to evaluate the frequency of isolation of Rhodotorula spp. in environmental samples of hospital origin in order to highlight how its presence may represent an increased risk for hospitalised patients. The samples were taken in at-risk wards, divided into six types of environments, in three hospitals in southern Sardinia between 2016 and 2019. The presence of moulds and yeasts was higher in the air (55.7%) than on surfaces (44.3%) in the hospital environments (p < 0.001). Similarly, the isolation frequency of Rhodotorula spp. was found to be greater (p < 0.001) in the air (14.2%) than on surfaces (9.2%). This study made it possible to evaluate the presence of pathogenic fungi in hospital environments, paying particular attention to Rhodotorula spp. since it is an emerging opportunistic yeast. It also highlights the importance of control measures especially in those where immunocompromised patients are present.

Ranking of Sustainable Medical Tourism Destinations in Iran: An Integrated Approach Using Fuzzy SWARA-PROMETHEE

Today, medical tourism is one of the fastest growing sectors of the tourism industry around the world. Medical tourism can contribute to the sustainable development and economic dynamism of countries. Therefore, in this study, we prioritize the world’s leading countries in medical tourism for Iranians. First, five main criteria and 20 sub-criteria were selected, which are the reasons for choosing a country as a medical tourism destination. In this paper a combined fuzzy SWARA-PROMETHEE approach was used to prioritize tourism destinations. The acronym PROMETHEE stands for Preference Ranking Organization Method for Enrichment Evaluation method and represents an useful MCDA (Multi-Criteria Decision Analysis) tool. On the other hand, SWARA acronym means Step-wise Weight Assessment Ratio Analysis. The criteria were weighted using the fuzzy SWARA approach. In the following, using the PROMETHEE approach, we prioritized eight countries as tourism destinations, then we identified criteria related to sustainability of medical tourism destinations and prioritized medical tourism destinations using these criteria as the contributions of this paper. The weights obtained for criteria “Abilities of skilled staff,” “Applied medical equipment,” “Marketing capability,” “Type of service provided,” and “Application of information and communications technology” were 0.176, 0.232, 0.108, 0.395, and 0.089, respectively. The results show that medical tourism destination priorities for Iranians are India (Phi = 0.1396), Malaysia (Phi = 0.1128), Panama (Phi = 0.0976), Mexico (Phi = 0.0790), Singapore (Phi = 0.0096), Taiwan (Phi = −0.0442), Brazil (Phi = −0.1747), and Costa Rica (Phi = −0.2196), respectively. Negative Phi values indicate below average performance of those countries and positive Phi values indicate above average performance of those criteria. The results indicate that countries with negative Phi values should be strengthened relative to the improvement of some criteria.

Hybrid Hesitant Fuzzy Multi-Criteria Decision Making Method: A Symmetric Analysis of the Selection of the Best Water Distribution System

Every country’s influence and livelihood is centered on that country’s water source. Therefore, many studies are being conducted worldwide to improve and sustain water resources. In this research paper, we have selected and researched the water scheme for groundwater recharge and drinking water supply of drought prone areas. The water project is aimed at connecting the drought prone areas of the three districts of Tamil Nadu to filling up the ponds in their respective villages and raising the ground water level and meeting the drinking water requirement. We have chosen a multi-criteria decision method to select the best alternative in a complex situation. When reviewing the implementation of this water project, many experts and people who will benefit from this project may have some hesitation and ambiguity in their suggestion on choosing the best water distribution system.We believe that the benefits of this project can be fully availed of if we choose a water distribution system. Our contribution in this article is to choose the best water distribution system for this project by use of our proposed multi-criteria decision making (MCDM) methods, hesitant fuzzy standard deviation with multi-objective optimization method by ratio analysis (HFSDV-MOORA), hesitant fuzzy standard deviation with technique, for order preference by similarity to an ideal solution (HFSDV-TOPSIS) and hesitant fuzzy standard deviation with VIsekriterijumsko Kompromisno Rangiranje (HFSDV-VIKOR), which will provide the best solution for improving the water resource for the drought-prone areas of three districts. Finally, we have identified and compared the correlation coefficient between proposed methods. As a result of the study, it has been found that the best water supply system is closed concrete pipes laid along agricultural land through the rural areas.

Fusing Multi-Attribute Decision Models for Decision Making to Achieve Optimal Product Design

Manufacturers need to select the best design from alternative design concepts in order to meet up with the demand of customers and have a larger share of the competitive market that is flooded with multifarious designs. Evaluation of conceptual design alternatives can be modelled as a Multi-Criteria Decision Making (MCDM) process because it includes conflicting design features with different sub features. Hybridization of Multi Attribute Decision Making (MADM) models has been applied in various field of management, science and engineering in order to have a robust decision-making process but the extension of these hybridized MADM models to decision making in engineering design still requires attention. In this article, an integrated MADM model comprising of Fuzzy Analytic Hierarchy Process (FAHP), Fuzzy Pugh Matrix and Fuzzy VIKOR was developed and applied to evaluate conceptual designs of liquid spraying machine. The fuzzy AHP was used to determine weights of the design features and sub features by virtue of its fuzzified comparison matrix and synthetic extent evaluation. The fuzzy Pugh matrix provides a methodical structure for determining performance using all the design alternatives as basis and obtaining aggregates for the designs using the weights of the sub features. The fuzzy VIKOR generates the decision matrix from the aggregates of the fuzzified Pugh matrices and determine the best design concept from the defuzzified performance index. At the end, the optimal design concept is determined for the liquid spraying machine.

Fuzzy Multicriteria Modelling of Decision Making in the Renewal of Healthcare Technologies

In the current literature, there are a clear lack of systems to assist in making decisions about the renewal of technology for healthcare equipment, which means that the limited capacity to invest in new equipment cannot usually be appropriately applied as determined by the care requirements of a community. This may have important repercussions for patients, such as the inability to offer treatment or diagnosis, having to delay treatment or diagnosis, increase the risk of patients and care staff of using obsolete equipment, and preventing early, accurate, and reliable diagnosis, all of which have effects on the quality of care to a community. This study therefore describes the first multicriteria model in a fuzzy environment to assist in decision making related to the renewal of healthcare equipment. The fuzzy analytic hierarchy process (FAHP), which allows for ambiguities, uncertainties, and doubts inherent in real-world decision processes to be taken into account, was used to do this. The model produces a plan with actions to be taken depending on the obtained results. The model includes a novel methodology that consists of modifying the top–down technique to allow for the levels of priority for renewing healthcare equipment to be determined from judgements given by three experts. The model was validated by applying it to a set of medical devices, and we show the results for a surgical C-arm, an X-ray CT room, a neonatal ventilator, a defibrillator, and a video-colonoscope. A program was also created using the NI Labview software to process the model so that it could be applied with a user interface that acts quickly, simply, and intuitively.

Supplier Selection for Photovoltaic Module Installation Utilizing Fuzzy Inference and the VIKOR Method: A Green Approach

The necessary transformation of the world’s energy matrices has led to a growth in developing technologies based on renewable sources. In this context, photovoltaic panels and their components count in Brazil with a production and commercialization chain that has accumulated a sustained growth of more than 100% of its generation capacities between the years 2018 and 2019, and that can fulfill or overcome this rate in 2019 to 2020. However, the conditions of a competitive market and the availability of a significant number of middle and small companies for the distribution and installation of photovoltaic technology may represent a scenario where multiple indicators must be considered. The purpose of this study is to apply a combined method to aid decision-making that corresponds to the supplier selection of the technology in the context of Northeast Brazil. The method is composed by the combination of a diffuse inference technique together with a multicriteria decision-making method, VIKOR, and the weight assignment to the indicators using the entropy method, according to the values of the decision matrix resulting from the diffuse inference technique that allows to develop the calculus. The results show that data collection from multiple sources and based on input variables can offer metrics about the suppliers for the selection criteria. Restrictions derived from data collection can be a barrier, and the method relies on an adapted script that facilitates application.

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.

Evaluating mobile services using integrated weighting approach and fuzzy VIKOR

Mobile services' rapid evolution and development has meant that their evaluation has become a more and more pressing issue, and from both the practical and theoretical standpoints. The significant previous work in the field of multiple-criteria decision-making based evaluation of mobile services has some practical limitations that should be noted. First, there has been insufficient research that has utilized both objective and subjective weighting. Second, the investigations that have employed Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), a well known practical tool for use in multi-criteria decision making, did not consider the fuzzy environment. In order to fill these gaps in the literature, the present study developed fuzzy VIKOR for use with an integrated weighting approach that combines subjective and objective weighting to account for mobile services' various characteristics and, thereby, evaluate their quality. For subjective weighting, Decision Making Trial and Evaluation Laboratory (DEMATEL) was employed for simple determination of the weighting and causal relationships. For objective weighting of evaluation criteria, Shannon entropy was utilized. This study has a unique contribution in that it reflects the special circumstances of the mobile service evaluation that have not been considered in the previous studies. Especially, in this study, not only the subjective weighting method but also the objective weighting method are used for more accurate importance weight of evaluation criteria. In the novelty aspect, this is the first study trying to utilize fuzzy VIKOR in concert with a novel combined subjective/objective weighting method in order to integrate objective decision-matrix-derived information with subjective decision-maker preferences. Additionally, a supplemental, empirical mobile-service-evaluation case study was conducted that enables researchers and practitioners to better understand the overall, practical evaluation process. Validation of the case study results by comparison with other, representative multiple-criteria decision-making methods verified the proposed method's robustness.

Developing the fifth generation port concept model: an empirical test

Purpose

The purpose of this paper is to test the 5GP concept with measurement of the performance of Busan, Hong Kong, Singapore and Shanghai ports, employing a hybrid method of consistent fuzzy preference relation (CFPR), VIsekriterijumska Optimizacija i KOmpromisno Resenje (VIKOR) and PROMETHEE.

Design/methodology/approach

The authors developed the concept of the fifth generation ports (5GPs), and apply CFPR, VIKOR and preference ranking organization method for enrichment evaluations (PROMETHEE) to evaluate the 5GPs.

Findings

The performance of the ports of Hong Kong and Singapore is close to meet the definition of 5GP criteria. On the contrary, ports of Busan and Shanghai are still behind the 5GP stage in light of the majority of the evaluation criteria’s performance.

Research limitations/implications

This paper studies four ports. More empirical tests are needed to verify the applicability of the 5GP concept toward other ports.

Practical implications

The findings provided port managers with the insight of how to improve their port to meet the criteria of 5GP.

Social implications

New criteria and higher expectations of existing requirements present challenges to port managers for a need to raise the bar of service standards and develop new competencies.

Originality/value

The authors developed the concept of the 5GPs. Newly developed 5GP contributes to expanding the concepts of first to fourth generation ports developed by UNCTAD.