scholarly journals MOORA under Pythagorean Fuzzy Set for Multiple Criteria Decision Making

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Luis Pérez-Domínguez ◽  
Luis Alberto Rodríguez-Picón ◽  
Alejandro Alvarado-Iniesta ◽  
David Luviano Cruz ◽  
Zeshui Xu

The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision-making (MCDM) problem. At the same time, the multiple criteria problem includes a set of decision makers with diverse expertise and preferences. In fact, the literature lists numerous approaches to aid in this problematic task of choosing the best alternative. Nevertheless, in the MCDM field, there is a challenge regarding intangible information which is commonly involved in multiple criteria decision-making problem; hence, it is substantial in order to advance beyond the research related to this field. Thus, the objective of this paper is to present a fused method between multiobjective optimization on the basis of ratio analysis and Pythagorean fuzzy sets for the choice of an alternative. Besides, multiobjective optimization on the basis of ratio analysis is utilized to choose the best alternatives. Finally, two decision-making problems are applied to illustrate the feasibility and practicality of the proposed method.

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Bahram Farhadinia ◽  
Atefeh Taghavi

The probabilistic hesitant fuzzy set (PHFS) is a worthwhile extension of the hesitant fuzzy set (HFS) which allows people to improve their quantitative assessment with the corresponding probability. Recently, in order to address the issue of difficulty in aggregating decision makers’ opinions, a probability splitting algorithm has been developed that drives an efficient probabilistic-unification process of PHFSs. Adopting such a unification process allows decision makers to disregard the probability part in developing fruitful theories of comparison of PHFSs. By keeping this feature in mind, we try to introduce a class of score functions for the notion of the single-valued extended hesitant fuzzy set (SVEHFS) as a novel deformation of PHFS. Interestingly, a SVEHFS not only belongs to a less dimensional space compared to that of PHFSs but also the proposed SVEHFS-based score functions satisfy a number of interesting properties. Eventually, some case studies of multiple criteria decision-making (MCDM) techniques under the PHFS environment are provided to demonstrate the effectiveness of proposed SVEHFS-based score functions.


2012 ◽  
Vol 17 (4) ◽  
pp. 645-666 ◽  
Author(s):  
Violeta Keršulienė ◽  
Zenonas Turskis

The philosophy of decision making in economics is to assess and select the most preferable solution, implement it and to gain the biggest profit. Important issues such as competitive market, changing technical, political and social environment have a key role in personnel selection. It is the crucial task which determines the company's present and future. Many decisions made cannot be accurately forecast or assessed. Understanding of the multiple criteria method and knowledge to calculate the algorithm of the method allows a decision maker to trust solutions offered by solution support systems to a greater extent. Many individual attributes considered for personnel selection such as organizing ability, creativity, personality, and leadership exhibit vagueness and imprecision. The fuzzy set theory appears as an essential tool to provide a decision framework that incorporates imprecise judgments inherent in the personnel selection process. In this paper, a fuzzy multi-criteria decision making (MCDM) algorithm using the principles of fusion of fuzzy information, additive ratio assessment (ARAS) method with fuzzy numbers (ARAS-F) and step-wise weight assessment ratio analysis (SWARA) technique are integrated. The proposed method is apt to manage information assessed using both linguistic and numerical scales in a decision making problem with a group of information sources. The aggregation process is based on the unification of information by means of fuzzy sets on a basic linguistic term set. The computational procedure of the proposed framework is illustrated through an architect's selection problem. Santrauka Sprendimų priėmimas ekonomikoje pagrįstas galimų sprendinių įvertinimu, tinkamiausio sprendinio atrinkimu, įgyvendinimu ir didžiausio pelno gavimu. Tokie svarbūs klausimai, kaip užsitikrinti vietą konkurencingoje rinkoje, besikeičianti techninė, politinė ir socialinė aplinka, yra vieni svarbiausių parenkant personalą. Tai labai svarbus uždavinys, tiesiogiai veikiantis bendrovės gyvavimą dabar ir ateityje. Daug sprendinių negali būti tiksliai prognozuojami arba įvertinti. Supratimas apie daugiatikslius metodus ir skaičiavimo metodo algoritmo išmanymas yra prielaidos sprendimų priėmėjui pasitikėti sprendiniais, kuriuos pateikia sprendimų priėmimo sistemos. Yra pateikiama daug atskirų rodiklių personalui atrinkti: organizaciniai gebėjimai, kūrybiškumas, asmeninės ir lyderio savybės. Visi šie rodikliai turi vieną bendrą savybę – jie negali būti tiksliai apirėžti. Tokiems uždaviniams spręsti neraiškiųjų aibių teorija gali pateikti sprendimo būdus, kurie įvertina netikslumus, būdingus personalo atrankos procesui. Šiame straipsnyje neraiškusis daugiatikslis sprendimų priėmimo (MCDM) algoritmas, taikant neraiškiosios informacijos sintezės principus, suminį santykinių dydžių vertinimo (ARAS) metodą, kurio reikšmės aprašomos neraiškiaisiais skaičiais (ARAS-F), ir laipsnišką rodiklių svorio santykinių dydžių analizės (SWARA) metodą, yra integruotas. Siūlomas metodas tinkamas informacijai, vertinamai tiek žodžiais, tiek skaitmenimis, išreiškiamoms skalėms, uždaviniui, kurio informacija surenkama iš grupės informacijos šaltinių, apdoroti. Sujungimo procesas grindžiamas informacija, taikant neraiškiųjų aibių teoriją pagrindinėms žodžiais aprašomoms reikšmėms pakeisti. Siūlomo algoritmo taikymas pavaizduotas sprendžiant architekto parinkimo uždavinį.


2005 ◽  
Vol 13 (1) ◽  
pp. 23-56 ◽  
Author(s):  
Badredine Arfi

In this article I use linguistic fuzzy-set theory to analyze the process of decision making in politics. I first introduce a number of relevant elements of (numerical and linguistic) fuzzy-set theory that are needed to understand the terminology as well as to grasp the scope and depth of the approach. I then explicate a linguistic fuzzy-set approach (LFSA) to the process of decision making under conditions in which the decision makers are required to simultaneously satisfy multiple criteria. The LFSA approach is illustrated through a running (hypothetical) example of a situation in which state leaders need to decide how to combine trust and power to make a choice on security alignment.


2020 ◽  
Vol 26 (1) ◽  
pp. 103-134 ◽  
Author(s):  
Huchang Liao ◽  
Hongrun Zhang ◽  
Cheng Zhang ◽  
Xingli Wu ◽  
Abbas Mardani ◽  
...  

As a generalized form of both intuitionistic fuzzy set and Pythagorean fuzzy sets, the q-rung orthopair fuzzy set (q-ROFS) has strong ability to handle uncertain or imprecision decisionmaking problems. This paper aims to introduce a new multiple criteria decision making method based on the original gain and lost dominance score (GLDS) method for investment evaluation. To do so, we first propose a new distance measure of q-rung orthopair fuzzy numbers (q-ROFNs), which takes into account the hesitancy degree of q-ROFNs. Subsequently, two methods are developed to determine the weights of DMs and criteria, respectively. Next, the original GLDS method is improved from the aspects of dominance flows and order scores of alternatives to address the multiple criteria decision making problems with q-ROFS information. Finally, a case study concerning the investment evaluation of the BE angle capital is given to illustrate the applicability and superiority of the proposed method.


Author(s):  
Reza Farzipoor Saen

Supplier selection is a multiple criteria decision making problem that the selection process mainly involves evaluating a number of suppliers according to a set of common criteria for selecting suppliers to meet business needs. Suppliers usually offer volume discounts to encourage the buyers to order more. To select suppliers in the presence of both volume discounts and imprecise data, this chapter proposes an optimization method. A numerical example demonstrates the application of the proposed method.


2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
M. Sarwar Sindhu ◽  
Tabasam Rashid ◽  
Agha Kashif ◽  
Juan Luis García Guirao

Probabilistic interval-valued hesitant fuzzy sets (PIVHFSs) are an extension of interval-valued hesitant fuzzy sets (IVHFSs) in which each hesitant interval value is considered along with its occurrence probability. These assigned probabilities give more details about the level of agreeness or disagreeness. PIVHFSs describe the belonging degrees in the form of interval along with probabilities and thereby provide more information and can help the decision makers (DMs) to obtain precise, rational, and consistent decision consequences than IVHFSs, as the correspondence of unpredictability and inaccuracy broadly presents in real life problems due to which experts are confused to assign the weights to the criteria. In order to cope with this problem, we construct the linear programming (LP) methodology to find the exact values of the weights for the criteria. Furthermore these weights are employed in the aggregation operators of PIVHFSs recently developed. Finally, the LP methodology and the actions are then applied on a certain multiple criteria decision making (MCDM) problem and a comparative analysis is given at the end.


2020 ◽  
Vol 9 (11) ◽  
pp. 9803-9811
Author(s):  
R. Sophia Porchelvi ◽  
V. Jayapriya

Pythagorean fuzzy set is an extension of Intutionistic fuzzy set, which is more capable of expressing and handling the uncertainty under uncertain environments, so that it was broadly applied in various fields. In this paper, we explored the concept of Pythagorean fuzzy multi set (PFMS). We describe some basic set operations of Pythagorean fuzzy multi set and also, we proposed sine exponential distance function. Finally, through an illustrative example it is shown how the proposed distance works in decision-making problem.


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