Preference Ranking Organization Method For Enrichment Evaluations Method Research Articles

Penentuan Tingkat Kompetensi Soft Skill Mahasiswa Menggunakan Metode Analytical Hierarchy Process dan Promethee

Bureau of Student Advisory Center (BSAC) Universitas Pembangunan Panca Budi is a center for career development and character building for students. In this case, a soft skill seminar is conducted to find the best candidate employees in the field of recruitment offered based on the criteria of student soft skill training. Determining the level of soft skill competences of students using the Analytical Hierarchy Process (AHP) method and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). For decision support systems using the AHP and PROMETHEE methods in determining the level of soft skill competencies, in order to obtain prospective employees who have the required soft skill competency level. Data collection was carried out by conducting research. The data is taken from the seminar results with 100 participants. The data that has been collected, processed and analyzed before being used as input and output as a basis for learning or training using the AHP and Promethee methods. Based on the calculations of the two methods, namely the AHP and Promethee methods, there are differences in calculations. In other words, because Promethee does not support the determination of weights and the hierarchy of criteria and does not have the assurance of consistency when determining weights like AHP. So that the program execution has a different time in the results, in the AHP method, program execution until the final result is obtained is better than the Promethee method. AHP has advantages in determining weights and criteria hierarchy, while Promethee has advantages in the alternative ranking process using different preference and weight functions.

Decision Support System for Employee Performance Evaluation with Promethe Method. Case Study: Faculty of Engineering, Pancasila University

High competent human resources can support the level of performance, by conducting performance evaluation assessments it will be known the achievements of each employee. Assessment of employee performance evaluation carried out by the Faculty of Engineering, University of Pancasila uses criteria of diligence, teamwork, sincerity to work, skills, initiative, independence and attendance. In this study, the authors used the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) to assist in making employee performance evaluation decisions, so that it can be seen which employees get the reward with good performance. The data used is in the form of employee performance evaluation data using six stages of the PROMETHEE method.

Sustainability assessment of healthcare waste treatment systems using surrogate weights and PROMETHEE method.

This study aims to assess the sustainability of healthcare waste treatment systems using surrogate weights and the Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE). For this purpose, ten treatment systems, including land disposal, incineration and non-incineration systems, were evaluated in terms of environmental, financial, social, and technical criteria. Firstly, fifteen reputed experts assigned their preferred rankings for the groups of criteria and the sub-criteria. The conversion of these rankings into numerical weights was performed using the SR function, which is an additive combination of Sum and Reciprocal weight functions. Secondly, the alternatives' performance with regards to each criterion allowed PROMETHEE to generate the outranking flows for each alternative. The complete ranking revealed that the rotary kiln (A4) is the most sustainable system followed by steam disinfection (A8), dry heat disinfection and microwave disinfection. However, the municipal landfill is the least sustainable system, while chemical disinfection is ranked in the penultimate position of sustainability. The partial ranking indicated that A4 and A8 are incomparable and both were ranked as most sustainable. Therefore, the sustainability of a system cannot be assessed properly without the exact specification of the system itself. In addition, it is preferable to act on the criteria that affect negatively the system to improve its performance.

A Combined AHP-PROMETHEE Approach for Intelligent Risk Prediction of Leak in a Storage Tank

This paper describes the use of the Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method for predicting the risk of leakage in a storage tank. This is the first time AHP and PROMETHEE have been used in this way. Important decisions about day to day operations are continually made in a petroleum environment. Storage tanks in refineries contain large volumes of flammable and hazardous liquids. Decision processes need to evaluate and select alternatives with a higher probability of resulting in a hazard, among many different alternatives. The new model described in this paper will aid decision-makers to predict which tank is likely to develop a leak and determine what criteria (source of risk) could result in a leak. Although the case study deals with a specific risk prediction problem, the combination of AHP and PROMETHEE methods can be applied to other decision problems.

Shifting to foot-and-mouth disease-free status without vaccination: Application of the PROMETHEE method to assist in the development of a foot-and-mouth national program in Uruguay

Foot-and-mouth disease (FMD) is highly contagious, and the introduction of FMD virus in countries free of the disease can result in large epidemics, similar to those observed in the United Kingdom, Japan, and Uruguay. Many countries or regions of South America are recognized as “FMD-free with vaccination” or “FMD-free without vaccination.” Uruguay has been certified as FMD-free with vaccination, and the transition to the status of FMD-free without vaccination has been discussed among the stakeholders of the Ministry of Livestock Agriculture and Fisheries (MGAP in Spanish). This study illustrates how the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) can identify and rank alternative actions to be used in the national FMD program in Uruguay. It uses multiple-criteria decision analysis (MCDA) to structure the problem comprehensively. This helps to identify critical issues and potential solutions when planning a national FMD program for a country with a disease-free without vaccination status. The analysis highlighted the following perspectives: i) the importance of communication strategies as the country changes to “FMD-free without vaccination” status, as well as potential challenges such as a lack of trust in government; ii) the importance of enhancing epidemiological capacity and data management to allocate resources better and provide feedback from the surveillance system; iii) the need to re-evaluate the animal health compensation strategy to stimulate biosecurity and disease reporting; and iv) the importance of assisting the backyard pig sector given the risks it carries and the complexity of dealing with because of its informality, the educational status of its owners, and the lack of formal assistance by veterinary services. The results suggests that the MCDA approach could be a useful tool for animal health agencies when planning a program to eliminate FMD (as well as other diseases) in a structured way because it helps to identify which alternatives would yield more effective results and it helps to address future challenges.

Sistem Pendukung Keputusan Pemilihan Sekolah SMA Swasta Terbaik Dengan Menggunakan Metode PROMETHEE Di Kota Pematangsiantar

Selection of the best private schools in embassy cities with the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method. This decision support system is built through 6 stages. The first stage is collecting data and information through interviews and document analysis. The second stage is processing data and information to get the system design to be built. The third stage is system analysis which includes school data input, weighting criteria with the PROMETHEE method, and alternative ranking with the PROMETHEE method. The Fourth stage is designing the system using the concept of Object Oriented Design. The fifih stage is the implementation of a web-based system. The last step is evaluating the system by comparing the level of accuracy between the PROMETHEE method. With the implementation of the PROMETHEE method for the selection of the best private schools that will result in the ranking of the best private schools, it is expected that in the selection of the best schools that are truly recommended in accordance with the wishes and abilities of students

Some new information measures for hesitant fuzzy PROMETHEE method and application to green supplier selection

Due to the increasing complexity and uncertainty in green supplier selection, there would be some hesitations for decision makers (DMs) to provide evaluation information of suppliers. Hesitant fuzzy set is a suitable tool to model such hesitations. This paper develops a hesitant fuzzy Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) for multi-criteria group decision-making and applies to green supplier selection. First, a new hesitancy index of hesitant fuzzy element (HFE) is defined. Then, a generalized hesitant fuzzy Hausdorff distance is proposed considering the individual deviation of membership values and the hesitancy index simultaneously. A combined hesitant fuzzy entropy is presented integrating the defined fuzziness entropy and hesitancy entropy of HFEs. Subsequently, a linear programming model is established to derive DMs’ weights objectively. To determine the criteria weights for each DM, a nonlinear programming model is built through minimizing the relative entropy. The PROMETHEE is employed to obtain individual ranking of alternatives for each DM. To obtain the collective ranking of alternatives, a multi-objective assignment model is constructed and transformed into a single-objective assignment model for resolution. Thereby, a hesitant fuzzy PROMETHEE method is presented. A green supplier selection example is demonstrated to validate the proposed method.

A decision framework of offshore wind power station site selection using a PROMETHEE method under intuitionistic fuzzy environment: A case in China

Multi-criteria decision-making (MCDM) method has a widely application in management and energy field. Considering the broad development prospects of offshore wind power and deficiency of integrated coastal management, a decision framework combining triangular intuitionistic fuzzy numbers (TIFNs), Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) is proposed and applied in site selection of offshore wind power station (OWPS). The aim of this study is to provide theoretical and methodological support for the site selection decision-making of coastal wind power projects and to improve the benefits of integrated coastal management. Taking six criteria (wind resources, construction, economic, environment, society, risk) and the related sub-criteria into consideration, an evaluation system of OWPS site selection is established. The optimal location scheme is determined by the decision framework in current paper. After a sensitivity analysis and a comparative analysis, the result shows that decision framework has strong robustness and feasibility. Thus, the evaluation criteria and methodology in this paper can provide a theoretical reference for the development of coastal management and offshore wind power.

Hybrid Use of Likert Scale-Based AHP and PROMETHEE Methods for Hazard Analysis and Consequence Modeling (HACM) Software Selection

Being a decision-making process, software evaluation and selection is complicated, time-consuming, costly and also critical to the success of the project/work/organization. In this study, evaluation and selection of customized software which are used to identify the physical effect (explosion, fire and toxic emission) distances for industrial establishments containing, using or storing hazardous chemicals has been considered. These software are called the “Hazard Analysis and Consequence Modeling” (HACM) software in the literature. This study first prepared Likert scale-based questionnaires which were distributed to Environmental Health and Safety (EHS) professionals to obtain their opinions. Likert scale was used with Analytic Hierarchy Process (AHP) method in the processing of data obtained from questionnaires in order to get over the inconsistency problem of pairwise comparison matrices. The Likert scale-based AHP method was used to determine the weights of the criteria, and Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE) method was used to obtain the final ranking. PROMETHEE method was preferred for having the opportunity of evaluating the binary “Yes–No” questions in the solution process. Finally, application results were given to illustrate the proposed method by using the PROMETHEE software “Visual PROMETHEE 1.4.0.0”.

A fuzzy multi-objective optimization approach for treated wastewater allocation.

In face of the new climate and socio-environmental conditions, conventional sources of water are no longer reliable to supply all water demands. Different alternatives are proposed to augment the conventional sources, including treated wastewater. Optimal and objective allocation of treated wastewater to different stakeholders through an optimization process that takes into account multiple objectives of the system, unlike the conventional ground and surface water resources, has been widely unexplored. This paper proposes a methodology to allocate treated wastewater, while observing the physical constraints of the system. A multi-objective optimization model (MOM) is utilized herein to identify the optimal solutions on the pareto front curve satisfying different objective functions. Fuzzy transformation method (FTM) is utilized to develop different fuzzy scenarios that account for potential uncertainties of the system. Non-dominated sorting genetic algorithm II (NSGA-II) is then expanded to include the confidence level of fuzzy parameters, and thereby several trade-off curves between objective functions are generated. Subsequently, the best solution on each trade-off curve is specified with preference ranking organization method for enrichment evaluation (PROMETHEE). Sensitivity analysis of criteria's weights in the PROMETHEE method indicates thatthe results arehighly dependent on the weighting scenario, and hence weights should be carefully selected. We apply this framework to allocate projected treated wastewater in the planning horizon of 2031, which is expected to be produced by wastewater treatment plants in the eastern regions of Tehran province, Iran. Results revealed the efficiency of this methodology to obtain the most confident allocation strategy in the presence of uncertainties.

Promethee Based Distributed Multihead Energy and Coverage Preserving Clustering Algorithm for Mobile Sensor Nodes

In this paper, a preference ranking organization method for enrichment evaluations (PROMETHEE) based distributed multihead energy and coverage preserving clustering algorithm for mobile sensor nodes (PDMECCA) is proposed. The objective of proposed PDMECCA is to equally distribute the load (communication, computation) among Mobile Sensor Nodes using the multihead concept for balancing the energy consumption among nodes and increase the lifetime of network with the ability to persistently provide coverage and connectivity of the entire monitored area. This paper considers PROMETHEE method for optimal selection of cluster heads based on multi criteria. The results of simulation show that proposed algorithm effectively prolongs the network lifetime and provide constant coverage persistently.

2-Dimension linguistic PROMETHEE methods for multiple attribute decision making

In multiple attribute decision making (MADM) problems, 2-dimension linguistic term set (2DLTS) is useful for modelling both the linguistic evaluations on alternatives and the decision makers’ self-assessments. This paper extends the preference ranking organization method for enrichment evaluations (PROMETHEE) methods to solve 2-dimension linguistic MADM problems. The extended PROMETHEE methods with 2DLTSs are mainly based on the improvement of the preference functions. For measuring two 2-dimension linguistic elements (2DLEs) in the improved preference functions, the possibility degree (PD) for 2DLEs is proposed to describe the PD of one 2DLE no less than another. It is shown that the PD for 2DLEs can measure the PD between two incomparable 2DLEs as well as two comparable 2DLEs. Furthermore, two examples are given to illustrate the effectiveness and flexibility of the proposed methods in solving the MADM problems evaluated by 2DLEs.

Neurocritical Care Unit Bed Allocation: Optimization Based on Prioritization Using Simulation

Background: Neurological trauma and diseases are the second cause of mortality and the main reason of acquired disability. Neurocritical care plays a major role in treating such patients. A longer life expectancy, treatment of incurable diseases, and limited resources available to add to hospital beds necessitates engineering the knowledge of health systems to prioritize allocation of current resources and present a proper pattern. Objectives: The current study aimed at optimizing bed use and shortening the length of patients` hospitalization in neurocritical care unit (NCCU) of Loghman Hakim hospital affiliated to Shahid Beheshti University of Medical Sciences, Tehran, Iran, and completely stimulating the procedure of bed allocation and prioritization of patients. Methods: Data of 420 patients hospitalized in NCCU was gathered and the procedure of bed allocation simulation was performed considering the priorities defined based on the length of hospitalization and patients’ chance of survival. The PROMETHEE (preference ranking organization method for enrichment evaluation) method was used to prioritize and allocate beds. To study the consequences of the suggested method, event discrete simulation tool was used to compare the current status and the results of the new method for 20 periods each including one month data. Results: The mean number of patients admitted to NCCU during one month without any prioritization was 76, while it increased to 86 based on prioritization. Conclusions: Patients’ simulation and prioritization using the PROMETHEE method resulted in 13% rise in the number of patients admitted to NCCU and higher utilization of this ward.

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.

Spatio-Temporal Multi-Criteria Optimization of Reservoir Water Quality Monitoring Network Using Value of Information and Transinformation Entropy

Identifying optimal Water Quality Monitoring Stations (WQMS) with high values of information on the entire reservoir status, instead of all potential WQMS would significantly reduce the monitoring network expenditure while providing adequate spatial coverage. This study presented a new methodology for spatio-temporal multi-criteria optimization of reservoir WQMS based on Value of Information (VOI), Transinformation Entropy (TE), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), and IRanian Water Quality Index (IRWQI). Although, all mentioned methods and concepts are well-known and have been used in water resources management, but their integration into a specific application for spatio-temporal multi-criteria optimization of reservoir WQMS is definitely an innovation and a contribution to improvement of WQMS design. More specifically, maximizing VOI as a decision-makers’ design criteria for optimization of WQMS, and considering spatial and temporal variations of water quality at different reservoir depths are new innovations in this research. The multi-objective optimization model was based on three objectives: 1) minimizing costs; 2) maximizing VOI; and 3) minimizing TE (redundant information). Considering these objectives, the NSGA-II multi-objective optimization method was used to find Pareto-optimal solutions. The most preferable solution was then determined using PROMETHEE multi-criteria decision making method. The proposed methodology was applied to Karkheh Reservoir with more than 5 billion cubic meter capacity and 60 km length that is one of the largest reservoirs in Southwestern Iran, however, the proposed approach has the ability to be generalized for any generic reservoir. Considering equal weights for criteria, PROMETHEE method resulted in 6 optimized WQMS out of 60 potential ones and a period of 25 days for optimal sampling interval. The optimized monitoring stations were mainly located at deep parts where most water quality variations are expected to occur. To show sensitivity of the model to different weights, 4 scenarios with various relative weights were evaluated in the PROMETHEE method. Results indicated that by increasing the weight of the second criterion (maximizing VOI), the number of optimized WQMS increased and the sampling interval decreased.

Optimal monitoring instruments selection using innovative decision support system framework

Structural monitoring is the most important part of the construction and operation of the embankment dams. Appropriate instruments selection for dams is vital, as inappropriate selection causes irreparable loss in critical condition. Due to the lack of a systematic approach to determine adequate instruments, a framework based on three comparable Multi-Attribute Decision Making (MADM) methods, which are VIKOR, technique of order preference by similarity to ideal solution (TOPSIS) and Preference ranking organization method for enrichment evaluation (PROMETHEE), has been developed. MADM techniques have been widely used for optimizing priorities and determination of the most suitable alternatives. However, the results of the different methods of MADM have indicated inconsistency in ranking alternatives due to closeness of judgements from decision makers. In this study, 9 criteria and 42 geotechnical instruments have been applied. A new method has been developed to determine the decision makers\' importance weights and an aggregation method has been introduced to optimally select the most suitable instruments. Consequently, the outcomes of the aggregation ranking correlate about 94% with TOPSIS and VIKOR, and 83% with PROMETHEE methods\'results providing remarkably appropriate prioritisation of instruments for embankment dams.

Using the PROSA Method in Offshore Wind Farm Location Problems

Wind is the most used renewable energy source (RES) in the European Union and Poland. Due to the legal changes in the scope of RES in Poland, there are plans to develop offshore wind farms at the expense of onshore ones. On the other hand, the success of an offshore wind farm is primarily determined by its location. Therefore, the aim of this study is to select offshore wind farm locations in Poland, based on sustainability assessment, which is an inherent aspect of RES decision-making issues. To accomplish the objectives of this research, PROSA (PROMETHEE for Sustainability Assessment) method, a new multi-criteria method is proposed. Like PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluation), PROSA is transparent for decision makers and is easy to use; moreover, it provides the analytical tools available in PROMETHEE, i.e., the sensitivity and GAIA (Geometrical Analysis for Interactive Assistance) analyses. However, PROSA is characterized by a lower degree of criteria compensation than PROMETHEE. Thus, it adheres in a higher degree to the strong sustainability paradigm. The study also compared the solutions of the decision problem obtained with the use of PROSA and PROMETHEE methods. The compared methods demonstrated a high concurrence of the recommended decision-making variant of location selection, from methodological and practical points of view. At the same time, the conducted research allowed to confirm that the PROSA method recommends more sustainable decision-making variants, and that the ranking it builds is less sensitive to changes in criteria weights. Therefore, it is more stable than the PROMETHEE-based ranking.

A fuzzy logic based PROMETHEE method for material selection problems

Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper presents a fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) method based on trapezoidal fuzzy interval numbers that can be applied to the selection of materials for an automotive instrument panel. Also, it presents uniqueness in making a significant contribution to the literature in terms of the application of fuzzy decision-making approach to material selection problems. The method is illustrated, validated, and compared against three different fuzzy MCDM methods (fuzzy VIKOR, fuzzy TOPSIS, and fuzzy ELECTRE) in terms of its ranking performance. Also, the relationships between the compared methods and the proposed scenarios for fuzzy PROMETHEE are evaluated via the Spearman’s correlation coefficient. Styrene Maleic Anhydride and Polypropylene are determined optionally as suitable materials for the automotive instrument panel case. We propose a generic fuzzy MCDM methodology that can be practically implemented to material selection problem. The main advantages of the methodology are consideration of the vagueness, uncertainty, and fuzziness to decision making environment.

Using multi-criteria decision making for selection provinces for fattening farm

Turkey has a high potential in the field of agriculture and livestock production. Turkey has a long history in the production of livestock system, which became the “buffer” sector of economy and the “locomotive” sector of Turkey. Although nowadays pastures are decreased, Turkey has quite large pastures. Besides, the domestic demand for meat in Turkey is quite large and tend to a show considerable growth. Animal husbandry is carrying great importance in terms of protein source and fattening cattle in the red meat production. In this sense, the development of meat production in terms of quality and quantity is also very necessary in terms of the nutritional problem that arises parallel to the growing population. In this study, the causes of increase in meat prices in Turkey were investigated, and the findings showed that, the cause of the price increases made as inadequate animal fattening. As a result, it was decided to establish a new place for the production of cattle-raising. Before starting the construction of the fattening livestock farm, firstly the location of the establishment is considered. In the decision-making process, it is quite difficult to make choices because of the different alternatives in terms of various criteria's. For this purpose, the PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) method, which is an easy and straightforward method of multi-criteria decision making techniques which are frequently used in researches in recent years, has been used to select the place of establishment in Turkey. The choice of fattening farm establishment site was evaluated in 81 provinces; cattle feed areas, demand on meat, urban development index value, average minimum temperature, average maximum temperature, precipitation amount and grant support criteria were evaluated with using the PROMETHEE method. The interactions between the criterion and the criteria that influence the process were determined as a result of the survey conducted. As a result of this survey study, criteria weights and criterion values were determined by Analytical Hierarchy Process (AHP) method and solved by PROMETHEE method considering the results. As a conclusion, the most suitable and the less suitable provinces for fattening livestock farm are selected

Multi-criteria decision analysis for sub-watersheds ranking via the PROMETHEE method

Soil and water resources are important elements of the environment that is managed to reduce the erosion rate and the destructive effects of torrential flooding. Implementation of the measures to reach this goal requires the ranking of sub-watersheds and areas within the sub-watersheds, from most to least vulnerable, which can be achieved using Multi-criteria decision analysis methods. In this paper, using the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) II method ranking of nine sub-watersheds delineated in the Topciderska river watershed, Serbia, was performed by using ArcGIS software. The criteria used for determining the order of the most vulnerable sub-watersheds are land cover, rainfall, soil erodibility as well as topography. The importance of criteria was determined by using the Analytic Hierarchy Process (AHP) method, and the influence of the criteria weights on ranking results was tested. This research identified that the most vulnerable sub-watershed is located in the upper part of the study area, where 15% of the territory is at high risk of erosion. Thus, this sub-watershed should have priority for protection through the implementation of appropriate measures and works. The results of the PROMETHEE II method and the ArcGIS application represent the valuable information for watershed management planning and implementation of soil erosion and torrent control measures.