scholarly journals An m-Polar Fuzzy PROMETHEE Approach for AHP-Assisted Group Decision-Making

2020 ◽  
Vol 25 (2) ◽  
pp. 26 ◽  
Author(s):  
Muhammad Akram ◽  
Shumaiza ◽  
José Alcantud

The Analytical Hierarchy Process (AHP) is arguably the most popular and factual approach for computing the weights of attributes in the multi-attribute decision-making environment. The Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) is an outranking family of multi-criteria decision-making techniques for evaluating a finite set of alternatives, that relies on multiple and inconsistent criteria. One of its main advantages is the variety of admissible preference functions that can measure the differences between alternatives, in response to the type and nature of the criteria. This research article studies a version of the PROMETHEE technique that encompasses multipolar assessments of the performance of each alternative (relative to the relevant criteria). As is standard practice, first we resort to the AHP technique in order to quantify the normalized weights of the attributes by the pairwise comparison of criteria. Afterwards the m-polar fuzzy PROMETHEE approach is used to rank the alternatives on the basis of conflicting criteria. Six types of generalized criteria preference functions are used to measure the differences or deviations of every pair of alternatives. A partial ranking of alternatives arises by computing the positive and negative outranking flows of alternatives, which is known as PROMETHEE I. Furthermore, a complete ranking of alternatives is achieved by the inspection of the net flow of alternatives, and this is known as PROMETHEE II. Two comparative analysis are performed. A first study checks the impact of different types of preference functions. It considers the usual criterion preference function for all criteria. In addition, we compare the technique that we develop with existing multi-attribute decision-making methods.

2021 ◽  
Vol 27 (1) ◽  
pp. 69-74
Author(s):  
Laila Oubahman ◽  
Szabolcs Duleba

Abstract In recent decades, decision support system has been constantly growing in the field of transportation planning. PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluation) method is an efficient decision-making support deployed in case of a finite number of criteria. It provides a partial ranking through PROMETHEE I and a complete ranking with PROMETHEE II. This outranking methodology is characterized by the elimination of scale effects between criteria and managing incomparability with the comprehensive ranking. However, PROMETHEE does not provide guidance to assign weights to criteria and assumes that decision makers are able to allocate weights. This review presents an overview of PROMETHEE models applied in transportation and points out the found gaps in literature.


2021 ◽  
Vol 12 (1) ◽  
pp. 75-90
Author(s):  
Anuja Shaktawat ◽  
Shelly Vadhera

Assessment of hydropower projects with respect to sustainability criteria is a multidimensional and complex issue. It requires considering technical, environmental, and social parameters instead of purely economic ones in decision making for energy planning. The flexibility to consider several criteria and objectives simultaneously leads to the use of multicriteria decision making (MCDM) methods which are well accepted in the field of energy planning. This paper aims at applying MCDM methods in facilitating the decision makers to select the most sustainable hydropower projects in the Indian region by making real and logical choices based on eight important criteria selected from the literature that are compatible with sustainable development. To comprehensively rank hydropower projects three MCDM methods are applied i.e., the technique for order of preference by similarity to ideal solution (TOPSIS), preference ranking organization method for enrichment evaluations (PROMETHEE II), and elimination and choice translating reality (ELECTRE III). Analytic hierarchy process (AHP) is used to calculate the weights of criteria. All three methods are well adapted for sustainability assessment and ranked Sharavathi (A9), Bhakra (A2), and Upper Indravati (A13) to be the most sustainable hydropower projects in India under the selected criteria. The study will be helpful in sustainable energy planning of hydropower projects with similar geographical conditions.


Author(s):  
Anuja Shaktawat ◽  
Shelly Vadhera

Assessment of hydropower projects with respect to sustainability criteria is a multidimensional and a complex issue that decision makers usually face during planning process. In hydropower projects, it is important to consider technical, environmental and social parameters instead of purely economic ones for sustainability assessment and decision making. Multi-criteria decision making (MCDM) methods offer a practical approach to a problem having conflicting criteria. The flexibility to consider several criteria and objectives simultaneously made MCDM methods well accepted in the field of energy planning. This paper aims for applicability of MCDM methods which will facilitate the decision makers to select the most sustainable hydropower projects by making real and logical choices based on various sustainability criteria. For comprehensively rank hydropower projects of Indian region based on sustainability criteria four MCDM methods are applied i.e., analytic hierarchy process (AHP), technique for order of preference by similarity to ideal solution (TOPSIS), preference ranking organization method for enrichment evaluations (PROMETHEE II) and elimination and choice translating reality (ELECTRE III). To ensure better decision making the eight criteria selected are compatible to the sustainable development of hydropower projects.


Author(s):  
Nayli Adriana Azhar ◽  
Nurul Asyikin Mohamed Radzi ◽  
Wan Siti Halimatul Munirah Wan Ahmad

: Multi Criteria Decision Making (MCDM) helps decision makers (DMs) solve highly complex problems. Accordingly, MCDM has been widely used by DMs from various fields as an effective and reliable tool for solving various problems, such as in site and supplier selection, ranking and assessment. This work presents an in-depth survey of past and recent MCDM techniques cited in the literature. These techniques are mainly categorised into pairwise comparison, outranking and distance-based approaches. Some well-known MCDM methods include the Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), Elimination et Choix Traduisant la Realité (ELECTRE), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Each of these methods is unique and has been used in a vast field of interest to support DMs in solving complex problems. For a complete survey, discussions related to previous issues and challenges and the current implementation of MCDM are also presented.


2021 ◽  
Author(s):  
Bhaba Krishna Mohanty ◽  
Eshika Aggarwal

Abstract This paper introduces a new methodology for solving Multi-Attribute Decision Making (MADM) problems under hesitant fuzzy environment. The uncertainty in Hesitant Fuzzy Elements (HFE) are derived by means of entropy. The resulting uncertainty is subsequently used in HFE to derive a single representative value (RV) of alternatives in each attribute. Our work transforms the RVs into their linguistic counterparts and then formulates a methodology for pairwise comparison of the alternatives via their linguistically defines RVs. The Eigen vector corresponding to maximum Eigen value of the pairwise comparison matrix prioritize the alternatives in each attribute. The priority vectors of the alternatives are aggregated to derive the weights of the attributes using Quadratic programming. The weighted aggregation of the attribute values provides the ranking of the alternatives in MADM. An algorithm is written to validate the procedure developed. The proposed methodology is compared with similar existing methods and the advantages of our method are presented. The robustness of our methodology is demonstrated through sensitivity analysis. To highlight the procedure a car purchasing problem is illustrated.


2014 ◽  
Vol 31 (04) ◽  
pp. 1450024 ◽  
Author(s):  
FARHAD SHAMS ◽  
SHERIF MOHAMED ◽  
AMINAH ROBINSON FAYEK

A typical approach to handle the complexity of multi-faceted decision-making problems is to use multi-attribute decision-making (MADM) methods based on pairwise comparisons. Fuzzy set theory has also been employed to cope with the uncertainty and vagueness involved in conducting the comparisons between components of a decision model. An important issue regarding the reliability of the output is the consistency of pairwise comparisons provided by the decision maker(s). Using the MADM method developed by Lu et al. (2007) as a foundation, this paper proposes an algorithm for evaluating the consistency level of pairwise comparison matrices, where linguistic data are used. A crisp numeric scale has been introduced to consider the priority of linguistic data and to avoid the complexity of handling fuzzy calculations in consistency evaluation of pairwise comparison matrices. As an advantage, the proposed method of consistency evaluation is capable of assessing the degree of inconsistency among the pairwise comparisons. Therefore, the acceptance or rejection of the pairwise comparisons can be determined based on the desired degree of tolerance in accepting inconsistent judgments. An application of a revised MADM method is then demonstrated in a case study involving flood mitigation project selection in Australia.


Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 77 ◽  
Author(s):  
Muhammad Akram ◽  
Shumaiza ◽  
Ahmad N. Al-Kenani

The preference ranking organization method for enrichment of evaluations (PROMETHEE) method considers a significant outranking class of multi-criteria decision analysis (MCDA), as it is easy to deal with its simple computations. In the PROMETHEE, different preference functions are used according to the type and nature of attributes or criteria that demonstrate the clearness and reliability of this method. This study provides a new version of the PROMETHEE method using bipolar fuzzy information, named the bipolar fuzzy PROMETHEE method. Bipolar fuzzy sets or numbers constitute an asymmetrical relationship between two judgmental factors of human reasoning. Vague and imprecise knowledge is characterized by bipolar fuzzy linguistic terms which are further represented in the form of trapezoidal bipolar fuzzy numbers. The trapezoidal bipolar fuzzy numbers are used by analysts to assign the preferences of alternatives on the basis of criteria. Further, a ranking function of bipolar fuzzy numbers is considered to access the crisp real preferences of alternatives. The entropy weighting information is employed to calculate the weights of attributes by considering the condition of normality. A numerical example such as the selection of green suppliers by using the bipolar fuzzy PROMETHEE is performed on the basis of the usual criterion preference function in order to explain the procedure of the proposed method. Comparable results are derived by using the combination of linear and level preference functions. The results obtained by using different types of preference functions are the same, representing the authenticity of the proposed bipolar fuzzy PROMETHEE method.


Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1816
Author(s):  
Dongsheng Xu ◽  
Xiaolan Wei ◽  
Hui Ding ◽  
Hongqiong Bin

Single-valued neutrosophic sets (SVNSs) can effectively describe the multi-attribute decision-making (MADM) problems which are characterized by incompleteness and uncertainty. Aiming at the MADM problem of SVNSs, a series of methods are proposed to solve the problem, such as the TODIM and PROMETHEE methods. The main idea of the TODIM method is to establish a relative superiority function of scheme relative to other schemes based on the value function of prospect theory, and the ranking of alternatives is determined according to the obtained superiority. In the PROMETHEE method, the decision maker selects the preference function for each attribute according to their preference, and then calculates the priority index, inflow, outflow and net flow according to the difference of the attribute values of scheme, so as to determine the ranking of alternatives. In this paper, a new method based on PROMETHEE and TODIM is proposed to solve the MADM problem under the single-valued neutrosophic environment. Based on the calculation formula of inflow and outflow in PROMETHEE method, and the calculation formula of overall dominance in the TODIM method, a new integrated formula is obtained.


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