Preference Ranking Organization Method For Enrichment Evaluation Research Articles

Sustainable Technology Supplier Selection in the Banking Sector

Sustainable supplier selection is a key strategic problem in supply chain management. The aim of this research is to provide a new hybrid multicriteria model for evaluating technology suppliers and validate it with a case study in the banking sector. This approach allows companies to perform qualification, selection, ranking and sorting of suppliers on a sustainable basis. Integration of several techniques is necessary to address this complex decision problem with conflicting economic, environmental and social criteria. Analytic hierarchy process (AHP) is useful for problem structuring and weighting criteria collaboratively. Multi-attribute utility theory (MAUT) is applied to obtain indicators for product quality and supplier risks, whose utility functions are derived by data-driven models that favour evaluation objectivity and transparency. Preference ranking organisation method for enrichment evaluation (PROMETHEE) is suitable for supplier selection due to its discriminant power among alternatives. Finally, FlowSort is proposed to classify suppliers into ordered groups and the outcomes are compared with results from MAUT. Results show its applicability by increasing process transparency and reducing operational risks in practice.

Selection of photodetectors in nuclear medical imaging using MCDM methods

Photodetectors used in nuclear medical imaging such as single photon emission computed tomography (SPECT) and positron emission tomography (PET) are an important element of radiation detection systems. Selecting the photodetector depends on many physical criteria including quantum efficiency (QE) and gain. The aim of this study is to apply multi-criteria decision-making (MCDM) methods to determine the optimum photodetector based on the evaluation and comparison of complex and multiple criteria. The photodetectors investigated in this study are photomultiplier tube (PMT), avalanche photodiode (APD) and silicon photomultiplier (SiPM). The bias voltage, gain, rise time, and QE were selected since they are considered as the key criteria for the photodetectors. Then, the corresponding values of each criteria were defined and preferred weights were assigned to each criteria based on the desired outcome. The fuzzy preference ranking organization method for enrichment of evaluations (PROMETHEE) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) methods were used to evaluate the alternatives. The results showed that conventional PMT came first in the ranking, followed by SiPM, while APD was the least desirable photodetector according to the fuzzy PROMETHEE and fuzzy TOPSIS methods based on the selected criteria and assigned weights. MCDM methods were used to select photodetectors used in PET and SPECT systems. One can incorporate as many alternatives and criteria as needed and assign the weights accordingly.

Integration of Analytic Network Process and PROMETHEE in Supplier Performance Evaluation

Supplier performance evaluation is one of the important factors in the supply chain because it is one of the company's strategies for increasing customer satisfaction and also maintaining the company's services in meeting consumer demand. This study proposes the integration of the Analytic Network Process (ANP) and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) to evaluate supplier performance. The integration of the two methods is proposed to obtain more complex assessment results because the combination of the two methods considers various criteria derived from ANP and various preferences from PROMETHEE, so both methods are very good to use instead of using just ANP or PROMETHEE or other methods. ANP exhibit more complex relationships between criteria and levels in the decision hierarchy, while PROMETHEE provides decision-makers with flexible and straightforward outranking to analyze multi-criteria problems. In this study, ANP is used to weight the criteria, and PROMETHEE is used to rank suppliers in evaluating supplier performance. Integrating these two methods provides more objective and accurate results in multi-criteria decision-making. The proposed method is validated by solving an industrial case of supplier evaluation problem using the real data from the skewer industry. Finally, some useful implications for managerial decision-making are discussed.

Pythagorean Fuzzy Sets Combined with the PROMETHEE Method for the Selection of Cotton Woven Fabric

ABSTRACT Identifying and selecting the best cotton fabric from a series of available samples is a challenging multicriteria decision-making (MCDM) problem that includes fuzziness and uncertainty. Pythagorean fuzzy sets (PFSs) are widely used to manage complex and uncertain MCDM issues. The Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) is a widely used classical MCDM to assess and rank alternatives. In this study, we use the PROMETHEE approach to solve a real case of ranking cotton fabrics in a PFS environment, where alternatives are compared based on the PFS linguistic scales, and a score function is used as a defuzzification function. A comparative analysis is also performed with different score functions. The ranking results of the proposed PF-PROMETHEE method correlate strongly with other score functions, which indicates that the PF-PROMETHEE method is feasible and effective. The salient contributions of the PF-PROMETHEE method are as follows: (1) the method can manage uncertainty better than other methods; (2) uncertainty is evaluated by linguistic scales in the PF environment; (3) the method can effectively select cotton woven fabric; and (4) the method is applicable to a wide variety of MCDM problems in the textile industry.

Bipolar fuzzy information‐based PROMETHEE‐based outranking scheme for mitigating vampire attack in wireless sensor networks

AbstractThe sensor nodes comprising sensing devices, small processing units, and battery, cooperate in wireless sensor networks (WSNs) for gathering potential factors that aids in achieving significant decision‐making processes in deployed applications. WSNs are vulnerable to security threats due to their open nature, availability characteristics, and lack of energy, resulting in a diversified number of security attacks. Among the security attacks, vampire attack is the serious threat as they drain the energy of nodes, which in turn crumbles the network lifetime and energy stability in WSNs. In this article, Bi‐Polar Information‐Based Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE)‐based outranking scheme is proposed for detecting and isolating vampire attacks to improve throughput with minimized energy consumptions and delay for prolonging lifetime. This proposed BPFI‐POR scheme used bipolar information that facilitates an asymmetrical association between two decision making factors that influences the discrimination and selection of genuine nodes from vampire nodes during the routing process. It aids in characterizing precise and vague information through bipolar fuzzy linguistic terms that has the maximized probability of being represented as trapezoidal bipolar fuzzy numbers. It estimated the cooperation of intermediate sensor nodes' based on trapezoidal bipolar fuzzy numbers for determining their preference or selection using criteria that could be influenced during the routing process. It also used the ranking function for accessing the alternatives through crisp real preferences with entropy weighting information responsible for attributes weight computation. The simulation results of the BPFI‐POR scheme confirmed better throughput, detection time with minimized energy consumptions and latency on par with the competitive algorithms.

Uncertainty of Preferences in the Assessment of Supply Chain Management Systems Using the PROMETHEE Method

The use of Supply Chain Management (SCM) systems allows for the improvement of an organization’s operations. Companies use many Enterprise Resource Planning (ERP) systems that also include SCM functionalities. As a result, the selection of the right system to be used in the enterprise is a complex problem. The use of multi-criteria decision aid (MCDA) methods provides the possibility of system ordering in a ranking, based on an asymmetric preference relation, symmetric indifference and incomparability relations. The aim of the article is to evaluate ERP systems in terms of their support for SCM. The scientific contribution of the article is the study of the impact of various degrees of uncertainty of the decision-maker’s preferences on the evaluation results and the analysis of the impact of various approaches to the preferences of alternatives on the final ranking. An approach based on MCDA Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) was used for the study. The decision model uses 12 criteria, three different preference functions and two variants of the PROMETHEE method (I and II). In this way, a total of six rankings were built, and each of them includes seven systems, supporting the management of the supply chain. As a result of the study, it was found that the highest functionality in logistics is characterized by the Oracle E-Business Suite system, which is more functional than SAP ERP and JD Edwards EnterpriseOne. The remaining analysed systems offer much less functionality. The applied approach, which was possible with the use of various preference functions, allowed three different levels of uncertainty in the preferences of decision-makers to be taken into account in the study. Moreover, the application of two different variants of the PROMETHEE method made it possible for the obtained solution to take into account the uncertainty of positions taken by individual ERP systems in the final rankings.

Materials selection for choosing the best composite blend polymeric membrane for hydrogen/oxygen proton exchange membrane fuel cell

Aromatic sulfonated polymers as a suitable candidate for Nafion membrane in proton exchange membrane fuel cells are the subject of many research activities. It has proved that these polymers need higher ion exchange capacities to reach the same proton conductivities compared to the Nafion membrane, which is a result of their different microstructures. Accordingly, to compensate different microstructures in the Nafion and sulfonated aromatic substitutions, several composite blend membranes of poly(ether sulfone) (PES) and poly(ether ether ketone) (PEEK), including electrospun fibers of highly-sulfonated/non-sulfonated PEEK and PES polymers have prepared. For comparison, two membranes with a routine solution-casting technique also have been made. The membrane-electrode assemblies are tested in H2/O2 single-cell. Before that, characterization measurements have performed for all membranes. To select the best sample between prepared membranes, multi-criteria decision-making (MCDM) have used, and to achieve more reliable results, four techniques of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), COmplex PRoportional ASsessment of alternatives (COPRAS), and VIekriterijumsko KOmpromisno Rangiranje (VIKOR) have applied. According to the experiments and MCDM methods, composite blend membrane containing sulfonated electrospun fibers of PEEK in non-sulfonated PES matrix gains the best rank among all membranes.

Evaluation of supply sustainability of vaccine alternatives with multi-criteria decision-making methods.

The treatment of the COVID-19 epidemic, whose contagious features are changing day by day, is the most current problem today throughout of the world. In order to be protected from COVID-19 and reduce its spread, it is of great importance to follow the rules such as mask, distance and hygiene. In addition, one of the most important ways to prevent the epidemic is to develop population immunity. The most important tool in having population immunity is vaccination. During the COVID-19 pandemic, there have been problems in the supply process of many products in food and health sectors. Vaccine is also one of the most difficult tools to supply. In this context, the study focused on the selection of the vaccine provided by the countries within the scope of population vaccination studies. At the selection point, the criteria affecting the purchasing process were determined and the weights of these criteria were calculated using the AHP method. Then, the criteria weights obtained were used to rank the alternatives in an integrated manner in the Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The results of both methods were analyzed comparatively. According to the TOPSIS Method, the first alternative is Oxford-AstraZeneca for all countries, and BioNTech for all countries in the PROMETHEE method. The vaccine storage conditions criterion is the most important in vaccine supply. The criterion with the lowest importance is Supply Cost. It has been revealed that cost elements remain in the background under pandemic conditions. Vaccine evaluation studies and policy recommendations are presented by considering public health in the selection of vaccine alternatives.

Selection of sustainable lignocellulose biomass for second-generation bioethanol production for automobile vehicles using lifecycle indicators through fuzzy hybrid PyMCDM approach

Petroleum prices are increasing day by day due to the essential requirement of fuel to run automobiles, agricultural engines and standby power plants. More utilization of fossil fuels leads to global warming, environmental pollution, ozone depletion, and climate change. The second-generation ethanol is produced from various feedstock, including agricultural wastes and lignocellulose biomass sources doesn’t affect the food security in many countries and the blending of bio-ethanol in gasoline reduced the greenhouse gas emissions. As large quantity of Lignocellulose biomass is available in India; the present study aims to select sustainable Lignocellulose biomass for the production of second-generation ethanol in Indian context. Five Lignocellulose biomass (Sugarcane Bagasse, Rice straw, wheat straw, Moringa, and Vetiver) were identified and prioritized using Multi-Criteria Decision Making (MCDM) methodology. This study followed the Hybrid MCDM approach to prioritize the Lignocellulose biomass. Python-based Evaluation Based on Distance from Average Solution (PyEDAS) MCDM algorithm was developed, and the final ranking is compared with COmplex PRoportional ASsessment (COPRAS), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) & Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE). From the results, Vetiver grass ranked as the best alternative, and Sugarcane bagasse ranked as the worst alternative among five Lignocellulose biomass sources.

Allocation of Optimal PMUs for Power System Observability Using PROMETHEE Approach

Phasor measurement units (PMUs) are becoming a vital measurement device in wide-area monitoring, operation, and control. The allocation of PMU at each bus will make that bus directly observable. However, considering the high installation costs, it is not feasible to place PMU at each bus. Thus, placing the PMUs at optimal locations is extremely important. In this study, the Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE)-based multi-criteria decision-making (MCDM) technique has been applied for the optimal allocation of phasor measurement units (PMUs) with the aim of achieving full system observability. Along with the entire network observability, the proposed approach provides maximum measurement redundancy (MR) too. Unlike some previous popular MCDM techniques, the proposed approach obtains optimal PMU placement (OPP) solution without performing pruning operations. Different criterion has been formulated to construct a decision matrix (DM). This DM helps in calculating the net outranking flow (NOF) of all the buses during the PROMETHEE approach. Based on the maximum NOF value, the PMUs are placed at those buses. The proposed approach also considers the inclusion of zero injection buses (ZIBs). Further, cases such as single PMU outage and existence of conventional measurements have been considered while determining optimal locations of PMUs. The proposed algorithm is demonstrated on IEEE 14-bus, 30-bus, 57-bus, and 118-bus systems, one Indian practical utility, i.e., Northern Regional Power Grid (NRPG) 246-bus system, and larger Polish 2383-bus system. To prove the effectiveness of the proposed algorithm, it has been compared with some of the popular existing techniques.

Electric bus charging station site selection based on the combined DEMATEL and PROMETHEE-PT framework

Electric buses (EBs) are one of the most promising transportation modes to reduce air pollution and greenhouse gas emissions. With the promotion of EBs, the selection of EBs charging station (EBCS) site plays a key role in bus electrification. In order to deal with the information uncertainty and the complicated logical relationship between evaluation criteria, this paper establishes a combined framework of fuzzy decision-making trial and evaluation laboratory (DEMATEL), preference ranking organization method for enrichment evaluations (PROMETHEE) and prospect theory (PT) to evaluate EBCS sites. Firstly, the evaluation criteria system consisting of transportation, economy, technology, and environment for the EBCS site selection problem is established. Secondly, the fuzzy DEMATEL method is adopted to calculate the weights of EBCS evaluation criteria and analyze their causal relationships. Thirdly, the fuzzy PROMETHEE method with PT is combined to obtain the ranking of the alternative EBCS sites. Finally, based on the case study in Nanjing city, the proposed combined framework proves to be effectiveness and scalability. The numerical results show that the long-term influencing criteria (e.g., coordination with power grid planning, total investment cost), the net cause criteria and the criteria with strong mutual influence have great impact on EBCS site selection.

Performance evaluation of Asian major cruise terminals

Compared to cargo terminals, performance evaluation of cruise terminals sits in a backseat in the current port performance studies, particularly in the Northeast Asia. This paper aims to evaluate the performance of major cruise terminals in Asia, taking into account the important dimensions and criteria influencing cruise terminal development, and using primary data by experts' responses to a questionnaire survey. Complementary data are also acquired by field trips and interviews to find the hidden information that is not revealed from the set questions in the questionnaire survey. To tackle the multiplicity and uncertainty in the collected data, the hybrid of Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) and Consistent Fuzzy Preference Relation (CFPR) is employed to evaluate cruise terminal performance and highlight visual illustration of the test results. The findings provide useful insights for guiding cruise lines’ terminal selection and for aiding cruise terminals to benchmark their performance to effectively improve their service and maximize their overall performance.

Bioprospecting autochthonous marine microalgae strain from the Arabian Gulf Seawater, Kuwait for biofuel feedstocks

Bioprospecting programmes are the key to increasing the current portfolio of indigenous microalgal strains accessible for different applications in microalgal biotechnology. In this work, nine fastgrowing microalgal strains isolated from the Arabian/Persian Gulf coastal waters of Kuwait were evaluated for their potential as biofuel feedstocks. 18S rRNA gene sequencing showed that the strains belong to five different genera, namely, Chlorella, Nannochloris, Scenedesmus, Tetraselmis, and Nannochloropsis. In terms of the total lipid content, in comparison to the other strains, Tetraselmis sp. KUBS13G and Tetraselmis sp. KUBS16G displayed higher lipid contents of 29.56% dry weight (DW) and 26.13% DW, respectively, which were dominated by palmitic and oleic acids. Fuel properties calculated from the fatty acid methyl esters (FAMEs) by empirical equations were compared with EN14214 (European) and ASTM D6751-−02 (American) biodiesel standards. Multicriteria decision analysis (MCDA) methods, such as the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), were used to select suitable microalgae for biofuel feedstock based on their biodiesel fuel properties. Overall, the results suggested that the indigenous microalgal strain Tetraselmis, in particular Tetraselmis sp. KUBS37G, and Scenedesmus sp. KUBS17R are the most suitable strains for biofuel feedstock owing to their improved fuel properties, such as density (ρ) (0.88 g cm−3), low kinematic viscosity (3.1 mm2 s−1), high cetane number (54 and 56, respectively), high oxidation stability (14.6 hr and 14.8 hr), and cold-filter plugging point (1.0°C and -6.1°C).

On sustainable improvements of agricultural practices in the Bairrada region (Portugal)

The objective of this paper is to develop a framework to overcome problems of soil nutrient legacies and poor quality of water bodies raised by agricultural practices. A multicriteria decision analysis (MCDA) approach is proposed to evaluate different alternatives to help to define sustainable vineyard agricultural solutions. The methodology developed was applied to a basin in the north-central part of Portugal, the São Lourenço basin. The land cover of the basin consists predominantly of vines. A number of alternatives based on different vineyard management practices and land use are evaluated against environmental and socioeconomic criteria by means of the soil and water assessment tool (SWAT) model and considering information included in some databases. The preference ranking organization method for enrichment evaluation (PROMETHEE) outranking method is used to rank the alternatives and to evaluate weight stability intervals assigned to criteria. A supplementary analysis is performed by a different MCDA method (technique for order of preference by similarity to ideal solution (TOPSIS)), belonging to the family of compensatory methods, to provide additional insights to the decision makers. The results show the best and the worst alternatives for vineyard agricultural practices according to the weights assigned to the criteria. The sensitivity analysis of the weights indicated most stable ranking cases and the criterion that presents the narrow stability intervals. This work offers the opportunity to discuss comparisons between different types of agricultural practices and give insights for future developments of other areas where intensive vineyard cultivation is implemented.

Overseeing road safety progress using CV-PROMETHEE Ⅱ-JSS: A case study in the EU context

Overseeing road safety progress at regular intervals has and will continue to be advocated as the most promising means to achieve continuous safety improvement. Thus, a scientific approach that can be capable of doing so is disparately required. This study aims to propose a brand-new and efficient methodology for overseeing overall road safety progress at the regional level. To this end, CV-PROMETHEE Ⅱ-JSS, which seamlessly incorporates Coefficient of Variation (CV), Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), and Joint Singular value decomposition and Semi-discrete decomposition (JSS) in an integrative manner, is developed. Specifically, this is designed to combine the retrospective examination and benchmarking analysis in a comprehensive and systematic framework. Based on the proposed methodology, the road safety development of the European Union (EU) Member States is examined over the past decade (2010–2020), whilst simultaneously benchmarking safety performance looking forward to the next decade (2020–2030). As a result, a detailed picture of changes in road safety for each country is quantitatively depicted, providing policymakers with deeper insights into how progress was achieved. The appropriate benchmarks are also scientifically identified for each laggard member to use as a meaningful reference, which largely avoids the need for reinventing the wheel and trial and error approaches. This study provides the EU27 + 3 countries with a practical paradigm to perform both diagnostics and treatment to improve overall road safety levels in an effective way; supporting the government officials and policymakers in the charting of future strategic directions and intervention priorities, and helping them define ways to accelerate action on proven strategies and policies for better lives. Moreover, this study enriches the existing Multi-Criteria Decision-Making (MCDM) mechanism by introducing the CV-PROMETHEE Ⅱ-JSS, and implies its feasibility and effectiveness in future MCDM cases involving safety-related issues.

Model Evaluasi Kinerja Tanggung Jawab Sosial Lingkungan Perusahaan di Kota Bogor

Corporate Social Responsibility (CSR) is a critical partnership potential in regional development. This potential is currently not too significant in its role and contribution to growth in Bogor, considering that the number is still limited. The TJSLP Secretariat encourages the participation of all parties through the preparation of a mechanism for submitting community TJSLP to the company. The purpose of this research is to develop a model for evaluating CSRs performance, which can be used as a basis for making decisions for the recommendations of the Bogor City government to corporate partners who have CSR programs. The evaluation model uses the PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) method to see the feasibility of the proposal with several criteria, namely the suitability of the program with the RPJMD (K1), activity category (K2), and activity costs (K3). The research resulted in a weighted value of K1=0.50, K2=0.33, K3=0.17. That look the ranking of the most appropriate in terms of the policy is Proposal B (religious), G (health), C (spiritual), H (health), A ( health), K (sports), J (education), D (economy), E (economy), I (environment), F (background). The results of sensitivity analysis, Spearman's Rho correlation coefficient of 0.97, between the results of the PROMETHEE ranking before and after the change in the weight of the criteria indicate high consistency, which is far from subjectivity. This TJSLP performance evaluation model is helpful for the TJSLP secretariat to evaluate the implementation of the CSR program in Bogor City.

Penerapan Metode PROMETHEE-GAIA Dalam Pemeringkatan Perguruan Tinggi di Indonesia

The Ministry of Research, Technology and Higher Education has been conducting university rankings since 2015. The goal is to map or build Indonesian universities. This ranking is known as university clustering, and it is separated into two categories: non-vocational/academic institutions and vocational universities. The goal of this research is to create higher education clusters based on the four key indicators that have been identified. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) II decision model in Multi-Criteria Decision Making (MCDM) was employed, together with Geometrical Analysis for Interactive Aid (GAIA) as geometric analysis in the form of decision-making visualization. This investigation yields alternative 2 with a phi of 0.5125 as a compelling value, followed by alternatives 3 and 1. According to the data, the second university out of the five evaluated had the best performance based on the four weights of the Indonesian higher education clustering indicator.

An integrated framework for sustainable supplier development through supplier evaluation based on sustainability indicators

The chemical industry has growing importance in sustainability because of the potential adverse effects on the environment. Also, stakeholders emphasize many social issues besides environmental protection for the chemical industry. Relying on a solid supplier base has become the main prerequisite for chemical manufacturers to achieve environmental targets and fulfill stakeholders' expectations while remaining competitive. This study develops the Integrated Sustainable Supplier Evaluation & Development Framework (ISSED-F) to support chemical manufacturers with managing supplier relationships according to the economic, environmental, and social facets of sustainability. Although the literature is rife with evaluation models aiming to fulfill the supplier selection tasks, these models mostly ignore the developmental role of supplier evaluation. To remedy this gap, ISSED-F adopts a deductive and holistic approach from setting the criteria to setting the measurement structure, evaluating the suppliers, and developing the suppliers. Materiality analysis, Analytic Network Process (ANP), Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), and cluster analysis are the fundamental methods that constitute the ISSED-F structure. A case study presents the use of the ISSED-F in a transnational chemical manufacturer's supplier relationship management (SRM) process. The case company evaluates 69 suppliers and assigns development strategies to the relevant performance segments within the implementation. The successful implementation of ISSED-F shows that it can be a roadmap for chemical manufacturers to adopt sustainability practices and ensure continuous development in their supply chains.

Retracted] Preorder of Factors Affecting Oil Prices: Fuzzy PROMETHEE Approach

Oil is a highly demanded worldwide product as oil prices can have a major economic and social impact. There are many factors affecting oil prices, but little is known about which factor mostly influenced oil prices. To understand what caused the fluctuation of oil prices, the investigation leading up to the identification of the factors must be constructed. Thus, this paper attempts to explore the factors that might have contributed to oil prices and analyze them using the fuzzy preference ranking organization method for enrichment evaluation (PROMETHEE) method. In particular, the objective of this study is to rank the influential factors affecting oil prices with the consideration of a few criteria. The fuzzy PROMETHEE model comprises four criteria and five factors as the input information. A group of four experts are invited to provide an evaluation on scales of 1 to 5 of the importance of factors with respect to criteria. In computation, the evaluations are treated as triangular fuzzy numbers in which the uncertainty in data is dealt with amicably. This approach combines the advantages of transformation equation and nonarithmetic mean of the defuzzification method that transforms triangular fuzzy numbers into crisp numbers. The results indicate that “supply and demand” is the most influential factor in determining oil prices. Comparative analysis and future research directions are also discussed at the end of this paper.

Comparison and selection of patient follow-up systems for covid-19 pandemic patients

People have struggled with many infectious diseases throughout history. Today, the Covid-19 is being fought. One of the most important things for people who have or are at risk of getting Covid-19 is social isolation. Many countries resort to different ways to ensure social isolation. For this, remote patient monitoring systems have been developed. In this study, the problem of the selection of Covid-19 remote patient monitoring systems is discussed. Seven Wearable Health Technology (WHT) products were evaluated with a total of 10 criteria, including the important symptoms used in the patient tracking systems. The weights of 10 criteria determined by the Analytical Hierarchy Process (AHP) method were calculated, and these weights were used in the solution of The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), and Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) methods. WHT products were compared. As a result, the most appropriate patient follow-up system was determined. This study generates differences in terms of evaluating seven different products and ten criteria in total with MCDM methods. A more comprehensive evaluation has been made in the literature than the studies in this field.