Fuzzy Preference Ranking Organization Method For Enrichment Evaluation Research Articles

Inotrope Analysis for Acute and Chronic Reduced-EF Heart Failure Using Fuzzy Multi-Criteria Decision Analysis

Heart failure is a progressive disease that leads to high mortality rates if left untreated, and inotropes are a class of drugs used to treat a type of heart failure where patients have reduced ejection fraction (HFrEF). This study aims to utilize the Fuzzy-Preference Ranking Organization Method for Enrichment Evaluation (F-PROMETHEE), an effectively used multi-criteria decision making (MCDM) technique. To analyze the characteristics of the most often used inotropes for acute HFrEF and chronic HFrEF, we use the same parameters set with distinct importance factors and aims for each property and, therefore, mathematically demonstrate the strengths and weaknesses of each inotrope alternative. As a result, a detailed ranking list for each HFrEF class was obtained, with supplementary information on how each parameter contributed to the ranking of each inotrope. From these results, it was concluded that the F-PROMETHEE method is applicable for evaluating the risks and benefits of various inotropes to determine a starting point for treating an average patient when making a quick decision without complete patient data. As demonstrated in this study, it is possible to easily use the same data set and only change some preference parameters according to individual needs to produce patient-specific results. In this study, we showed that creating a decision-making system that mathematically assists clinical specialists with their decision-making process is feasible.

Fuzzy preference ranking organization method for enrichment evaluation‐based node cooperation technique for improving QoS in MANETs

SummaryCooperation between mobile nodes is the predominant factor required for achieving reliable data dissemination in mobile ad hoc networks (MANETs), since non‐cooperative nodes crumbles the routing process and degrades network performance. The degree of non‐cooperation rendered by mobile nodes need to be accurately identified by exploring feasible and comprehensive number of criteria to achieve maximized cooperation in uncertain MANET. In this paper, fuzzy preference ranking organization method for enrichment evaluation (FPROMETHEE)‐based node cooperation technique is proposed with the merits of trapezoidal fuzzy interval numbers that aids in the selection of high trustworthy mobile nodes for attaining maximized data delivery. This FPROMETHEE technique utilizes complex and multiple criteria for potential ranking in the presence of finite number of mobile nodes. It prevented the bias of information that is more common during the judgmental process associated with the cooperation estimation of mobile nodes. It includes information about the relative weights of criteria and decision maker's preferences for estimating the trust of mobile nodes to include or isolate them from the routing path. It is also useful in handling the degree of uncertainly involved in the process of routing without compromising Quality of Service (QoS) level in the network. The simulation experiments of the proposed FPROMETHEE technique conducted using ns‐2 simulator confirmed its predominance in enhancing the packet dissemination rate, throughput, energy consumptions, total overhead, and packet loss rate for different number of mobile nodes, malicious nodes, and pairs of source and destination nodes.

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.

Novel Fuzzy Composite Indicators for Locating a Logistics Platform under Sustainability Perspectives

The purpose of this paper is to help decision-makers choose the location of a logistics platform with sustainability perspectives. This study presents a compensatory and partially compensatory approach to build composite indicators, using mainly fuzzy multi-criteria decision-making methods. In the first instance, the fuzzy full consistency method (F-FUCOM) was used to calculate the weight of the criteria and sub-criteria. In the second instance, two aggregation methods, namely the fuzzy multi-attribute ideal-real comparative analysis (F-MAIRCA) and the fuzzy preference ranking organization method for enrichment evaluation (F-PROMETHEE), were used to rank the location of a logistics platform. The novelty of the work lays in studying the impact of limited sustainability and weak sustainability on the location of a logistics platform. In this respect, the aggregation of various sustainability criterion in fuzzy compensatory and partially compensatory composite indicators is an innovative and interesting approach used to locate a logistics platform. The obtained results show that economic sustainability is the most important criterion for the selection of a logistics platform, followed by the environmental criterion. Obviously, the F-MAIRCA and F-PROMETHEE methods provided the same ranking orders. Finally, sensitivity analyses were performed to validate the robustness of the proposed approach.

An integrated methodology for the selection of sustainable suppliers and order allocation problem with quantity discounts, lost sales and varying supplier availabilities

In this study, selection of sustainable suppliers (SSS) and order allocation (OA) problem is generalized by considering multi-product, multi-supplier and multi-period scenarios with quantity discounts, lost sales and varying supplier availabilities. The study is designed in four phases. In the first phase, suppliers are ranked by using integrated the Fuzzy Analytic Hierarchy Process (F-AHP) and fuzzy Preference Ranking Organization Method for Enrichment Evaluation (F-PROMETHEE) considering social and environmental factors as well as economic factors. The output of the first phase is used in the second phase of the method. In the second phase, a fuzzy multi-objective optimization (FMOO) model is proposed to find quantities to be purchased from suppliers. In the third phase, both the Augmented ε-constraint (AUGMECON) method and LP-metrics are used to obtain the Pareto front of the problem. Finally, in the fourth phase, a solution is selected by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) from the non-dominated solutions. The effectiveness of the proposed method is shown on real data from a firm selling medical devices.

Evaluate and Rank the Smartphone Brand Using Fuzzy AHP and PROMETHEE

A buying decision process is one of the Multi-Criteria Decision Making (MCDM) problems faced by everyone in daily life. One example is the selection of smartphones brand in the market. Thus, the study is conducted to evaluate the most effective criteria for buying smartphones and to rank the people's preferences on smartphone based on its brand. Six criteria (price, operating system, memory, display, camera and battery) and three alternatives which are the smartphone brands (Oppo, Samsung and Apple) were chosen in the study. Two main processes were involved, which are 1) evaluate the smartphone criteria using Fuzzy Analytic Hierarchy Process (AHP) and 2) ranking the brand using Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE). Surveys and questionnaires were conducted and evaluated by decision makers who are the smartphone's users. The result showed storage memory is considered as prominent criteria in choosing a smartphone meanwhile the consumers firstly prefer Oppo, secondly Apple and thirdly Samsung. Future work in this study may use other alternatives to be ranked by considering other top models as well.
 Keywords: Multiple criteria decision making, smartphone brand, Fuzzy AHP, Fuzzy PROMETHEE

Multi-criteria evaluation of renewable energy alternatives for electricity generation in a residential building

The residential sector is well known to be one of the main energy consumers worldwide. The purpose of this study is to select the best renewable energy alternatives for electricity generation in a residential building by using a new integrated fuzzy multi-criteria group decision-making method. In renewable energy decision-making problems, the preferences of experts and decision-makers are generally uncertain. Furthermore, it is challenging to quantify the reel performance of renewable energy alternatives using a set of exact values. Fuzzy logic is commonly applied to deal with those uncertainties.The method proposed in this paper combines different methods. First, the Delphi method is used in order to select a preliminary set of renewable energy alternatives for electricity generation as well as a preliminary set of criteria (economic, environmental, social, etc.). Then, the questionnaire is used to study the renewable energy alternatives preferences of the residents of the residential building’. Later, the FAHP (Fuzzy Analytical Hierarchy Process) is implemented to obtain the weighs of the criteria taking into consideration uncertainties in expert's judgments. Finally, the FPROMETHEE (Fuzzy Preference Ranking Organization Method for Enrichment Evaluation) global ranking is performed in order to get a complete ranking of the renewable energy alternatives taking into account uncertainties related to the alternatives' evaluations.The originality of this paper comes from the application of the proposed integrated Delphi- FAHP- FPROMETHEE methodology for the selection of the best renewable energy alternatives for electricity generation in a residential building. A case study has validated the effectiveness and the applicability of the proposed method. The results reveal that the proposed integrated method helps to formulate the problem and is particularly effective in handling uncertain data. It facilitates the selection of the best renewable energy alternatives in a manner that is participatory, comprehensive, robust, and reliable.

NEAT F-PROMETHEE – A new fuzzy multiple criteria decision making method based on the adjustment of mapping trapezoidal fuzzy numbers

The Fuzzy PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluation) method allows one to capture uncertainty and imprecision of input data of a decision problem as well as the uncertainty of the decision-maker's preferences. However, a considerable number of implementations of the Fuzzy PROMETHEE method are burdened with some imperfections related to, among other things, a high level of complexity, an applied computational procedure or the incompatibility with the classical PROMETHEE method paradigms. The article presents a new fuzzy MCDM method called NEAT F-PROMETHEE (New Easy Approach To Fuzzy PROMETHEE) characterized by low complexity, conformity with the methodological assumptions of the classical PROMETHEE method and the improvement of the process of mapping fuzzy numbers from a space X on Y with the use of the correction mechanism while mapping. Furthermore, other improvements have been introduced which are to simplify the computational procedure and increase its clarity for the sake of the decision-maker. The prepared method and its results have been compared to other Fuzzy PROMETHEE implementations, the classical PROMETHEE method as well as the Fuzzy TOPSIS method. In the research, it has been found out that the correction mechanism and other improvements applied in NEAT F-PROMETHEE make it possible to obtain a higher computational accuracy what results in a higher credibility of the solution of a decision problem in comparison with many other Fuzzy PROMETHEE implementations. The advantage of the prepared method over more complex implementations is its simplicity, easiness of application and interpretation of results. It has also been indicated that uncertainty of input data and uncertainty of the decision-maker's preferences are related to each other and the relationship is expressed by grouped relations of preferences, that is, preference, J-preference and outranking.

Decision-Support Framework for Selecting the Optimal Road Toll Collection System

One of the central decision-making questions in planning road tolling is the selection of the optimal toll collection system (TCS). The question of TCS selection arises in the situation when the existing TCS is to be upgraded or when TCS is selected for a newly constructed road. Considering that there are multiple TCS available nowadays, with their particular advantages and disadvantages, and that there is a range of often conflicting criteria for TCS selection, this decision-making issue belongs to the group of multicriteria decision-making (MCDM) problems. The MCDM-based methodology used in this research integrates Strengths-Weakness-Opportunities-Threat (SWOT) analysis and Fuzzy Preference Ranking Organization Method for Enrichment Evaluations (F-PROMETHEE). The expert-based decision-support framework includes a procedure for defining evaluation criteria and their weights, scoring of alternatives, and sensitivity analysis. Presented decision-support framework is tested with fourteen toll systems. Results indicate that the best-ranked TCS is the dedicated short-range communication multilane free flow. Decision-support framework is developed for transferability to different contexts, where local features can be taken into account by choosing specific alternatives, criteria, and criteria values. Finally, this development opens up opportunities for further analysis of criteria values and considerations of user attitudes in road pricing scheme planning.

An integrated fuzzy approach for prioritizing supply chain complexity drivers of an Indian mining equipment manufacturer by Kavilal, E. G., Venkatesan, S. P., Kumar, K. D. H., [Resour. Policy 51 (2017) 204–218]: Suggested modification

Kavilal et al. (Resour. Policy 51 (2017) 204–218) pointed out the limitations of the fuzzy preference ranking organization method for enrichment evaluation (FPROMETHEE) method. To overcome the limitations, Kavilal et al. proposed an effective approach by integrating the FPROMETHEE, fuzzy analytic hierarchy process (FAHP) and fuzzy interpretive structural modeling (FISM). To illustrate this approach, Kavilal et al. considered a case example of a mining equipment manufacturer located in India. In future, the other researchers may use this approach for solving other real life problems and /or in their research work. It is pertinent to mention that to apply the approach, proposed by Kavilal et al., there is need to apply FAHP and to apply FAHP, there is need to check that the fuzzy pairwise comparison matrix is consistent or not. To check the same, Kavilal et al. have transformed the fuzzy pairwise comparison matrix into a crisp matrix and claimed that the fuzzy pairwise comparison matrix will be consistent if the transformed crisp matrix will be consistent. However, after a deep study, it is observed that on applying the defuzzification method, used by Kavilal et al. to transform the fuzzy pairwise comparison matrix into a crisp matrix, the obtained transformed crisp matrix will never be consistent therefore, one may conclude that the FAHP cannot be applied. Hence, one may conclude that the approach, proposed by Kavilal et al., cannot be applied. Keeping the same in mind, an appropriate defuzzification method is suggested to transform the fuzzy pairwise comparison matrix into a crisp pairwise comparison matrix.

Evaluating X-Ray based Medical Imaging Devices with Fuzzy Preference Ranking Organization Method for Enrichment Evaluations

X-rays are ionizing radiation of very high energy, which are used in the medical imaging field to produce images of diagnostic importance. X-ray-based imaging devices are machines that send ionizing radiation to the patient’s body, and obtain an image which can be used to effectively diagnose the patient. These devices serve the same purpose, only that some are the advanced form of the others and are used for specialized radiological exams. These devices have image quality parameters which need to be assessed in order to portray the efficiency, potentiality and negativity of each. The parameters include sensitivity and specificity, radiation dose delivered to the patient, cost of treatment and machine. The parameters are important in that they affect the patient, the hospital management and the radiation worker. Therefore, this paper incorporates these parameters into fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) multi-criteria decision theory in order to help the decision makers to improve the efficiency of their decision processes, so that they will arrive at the best solution in due course.

Evaluating and selecting partners in sustainable supply chain network: a comparative analysis of combined fuzzy multi-criteria approaches

Partner selection is a crucial problem in supply chain management in which it is essential today to integrate sustainability criteria due to regulation, stakeholder pressers and economic interests. Thus, a sustainability-focused evaluation model for partner selection is required in order to improve the overall performance of the supply chain. This paper develops a new hybrid approach to evaluate and select the partners (suppliers and 3PRL providers) in sustainable supply chain network by combining Fuzzy Analytic Hierarchy Process (F-AHP) with Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (F-PROMETHEE), and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (F-TOPSIS). A set of sustainability criteria for both supplier and 3PRL provider selection is proposed based on extensive literature review and experts’ opinions. F-AHP is used to calculate the priority weight of each criterion. Then, F-PROMETHEE and F-TOPSIS are both used to rank the partners comparatively. The validity and efficacy of the proposed approach is demonstrated through an application for selecting partners in the case of light bulbs recycling which has been strengthened by sensitivity analysis.

An integrated fuzzy approach for prioritizing supply chain complexity drivers of an Indian mining equipment manufacturer

The complexities in present day supply chain are numerous and are evolving due to globalization, customisation, innovation, flexibility, sustainability and uncertainties. The growing supply chain complexity results in negative consequences on cost, customer service and reputation. Managing supply chain complexity without compromising the profitability is a challenging task. Supply chain complexity (SCC) management involves identifying, prioritizing, measuring, analysing and controlling/eliminating the drivers of complexity. The SCC drivers denote number and variety of suppliers, customers, products, processes and uncertainties which are highly interdependent. Firms need to prioritize the drivers in order to manage and simplify SCC. Models and methods to prioritize the complexity drivers considering their interdependence are limited in literature. Prioritizing the complexity drivers requires a subjective approach and it is a multi criteria decision making (MCDM) problem. In this research, at first a fuzzy ISM (Fuzzy Interpretive Structural Modelling) is used to establish the interdependence of SCC drivers. A fuzzy AHP (Analytic Hierarchy Process) and fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) are then used to quantify and prioritize the complexity drivers considering the strength of interdependence obtained using the fuzzy ISM. A case example of a mining equipment manufacturer located in India is presented to illustrate the proposed approach. From the results it is identified that unreliability of suppliers, forecast inaccuracy, lack of visibility /information sharing and number/variety of processes are the significant drivers.

An Extended Fuzzy PROMETHEE based on Fuzzy Rule based System for Supplier Selection Problem

Background/Objectives: Supplier Selection Problem (SSP) has become critical issue for purchasing department because of its significant effect toward successful logistic and Supply Chain Management (SCM). Due to the fact that various conflicted criteria must be considered, SSP is inherently Multiple Criteria Decision Making (MCDM) problem. Methods/Statistical Analysis: The aim of this paper is to solve SSP under group decision making and fuzzy environment. To do so, as main contribution of this paper, a hybrid approach which employs both Fuzzy Rule Based System (FRBS) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), is proposed to select suitable supplier. Findings: One advantage of MCDM techniques is providing Decision Maker's (DM) preferences and utilities. To do so, we have modeled DM's utilities using fuzzy logic and then implemented in PROMETHEE method. Improvement/Application: Ultimately, numerical illustration and sensitivity analyses are performed to demonstrate the applicability of the proposed method for a supplier selection problem.

LOGISTICS FREIGHT CENTER LOCATIONS DECISION BY USING FUZZY-PROMETHEE

Fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (F-PROMETHEE) was applied for choosing among potential logistics center locations. The method combines the concept of fuzzy sets to represent uncertain information with the PROMETHEE, a subgroup of Multi-Criteria Decision-Making (MCDM) methods. Criteria are identified based on review of scientific and trade literature and inputs received from experts. The suitability of areas have been evaluated on the basis of these criteria. There are substantial uncertainties and subjectivity about site information. Therefore F-PROMETHEE method is preferred. The case study shows that this application provides reasonable results.

Multi-criteria decision making with intuitionistic fuzzy PROMETHEE

This paper investigates one of the outranking based methods, PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), for multi-criteria decision making, and extends it into in...

A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

A fuzzy preference-ranking model for a quality evaluation of hospital web sites

This article presents a quality evaluation model for measuring the performance of hospital Web sites. The model is developed on the basis of a conceptual framework, which consists of seven major e-service quality dimensions, including tangibles, reliability, responsiveness, confidence, empathy, quality of information, and integration of communication issues of Web sites. The dimensions and their associated attributes are first obtained from published articles in the health care and information technology literature and then adapted according to the suggestions of related domain experts. Two multicriteria decision-making methods are used in the evaluation procedure. Determined Web site evaluation dimensions and their relevant attributes are weighted using the Analytic Hierarchy Process (AHP) method. Vagueness in some stages of the evaluation required the incorporation of fuzzy numbers in the assessment process. Both fuzzy and crisp data are then synthesized using the fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) ranking method. The model is applied initially to measure the performance of the Web sites of Turkish hospitals. This study should be of interest to health care and technology practitioners and researchers, as the findings shed light on the further development of performance measurements for hospital Web sites. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 1181–1197, 2006.