An Analysis for Selecting Best Smartphone Model by AHP-TOPSIS Decision-Making Methodology

Author(s):  
Shankha Shubhra Goswami ◽  
Dhiren Kumar Behera

This article presents the detailed study of integrated AHP-TOPSIS multiple-criteria decision-making (MCDM) methodology. For these purposes, a real-life example is taken where the best smartphone mobile model is proposed among 10 different available models by implementing integrated AHP-TOPSIS methodology. The 10 mobile models selected for this analysis are presently available in the market and are from different brands having different specifications and price range. The selection process is done based on four major criteria (i.e., price, internal storage, RAM, and brand). AHP is applied for the criteria weightage's calculation, whereas TOPSIS is adopted for selecting the best alternative and make a preference ranking order indicating the best model to the worst. The final result shows that Samsung J7 is the best smartphone model followed by Redmi 7A, and Redmi K20 pro occupies the last position; thus, it is the worst model among the group.

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.


2008 ◽  
Vol 25 (05) ◽  
pp. 715-733 ◽  
Author(s):  
M. A. YAGHOOBI ◽  
D. F. JONES ◽  
M. TAMIZ

Weighted additive models are well known for dealing with multiple criteria decision making problems. Fuzzy goal programming is a branch of multiple criteria decision making which has been applied to solve real life problems. Several weighted additive models are introduced to handle fuzzy goal programming problems. These models are based on two approaches in fuzzy goal programming namely goal programming and fuzzy programming techniques. However, some of these models are not able to solve all kinds of fuzzy goal programming problems and some of them that appear in current literature suffer from a lack of precision in their formulations. This paper focuses on weighed additive models for fuzzy goal programming. It explains the oversights within some of them and proposes the necessary corrections. A new improved weighted additive model for solving fuzzy goal programming problems is introduced. The relationships between the new model and some of the existing models are discussed and proved. A numerical example is given to demonstrate the validity and strengths of the new model.


JOURNAL ASRO ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 10
Author(s):  
Sutrisno Sutrisno ◽  
Sutikno Wahyu Hidayat ◽  
Avando Bastari ◽  
Okol Sri Suharyo

The recruitment process is the initial process that determines the sustainability and success of a company. In the process, effective and efficient selection tests are the key. The level of professionalism and academic ability of prospective employees are two things that are very much needed as a reference and criteria that are used as selection factors in the recruitment process. This study uses the Fuzzy Multiple Criteria Decision Making (MCDM) method by solving problems using the Simple Addictive Weighting Method (SAW). The use of this method is expected to produce an electronic selection test application that can help the recruitment team in carrying out the selection process at PT. X. The results of the research are in the form of prospective employee selection test applications to simplify the process of selecting prospective employees according to their needs.  Keywords: Selection Test, Application, FMCDM, SAW


2016 ◽  
Vol 5 (4) ◽  
pp. 192-210 ◽  
Author(s):  
Bhagawati Prasad Joshi

Due to the huge applications of fuzzy set theory, many generalizations were available in literature. Atanassov (1983) and Atanassov and Gargov (1989) introduced the notions of intuitionistic fuzzy sets (IFSs) and interval-valued intuitionistic fuzzy sets (IVIFSs) respectively. It is observed that IFSs and IVIFSs are more suitable tools for dealing with imprecise information and very powerful in modeling real life problems. However, many researchers made efforts to rank IVIFSs due to its importance in fusion of information. In this paper, a new ranking method is introduced and studied for IVIFSs. The proposed method is compared and illustrated with other existing methods by numerical examples. Then, it is utilized to identify the best alternative in multiple criteria decision-making problems in which criterion values for alternatives are IVIFSs. On the basis of the developed approach, it would provide a powerful way to the decision-makers to make his or her decision under IVIFSs. The validity and applicability of the proposed method are illustrated with practical examples.


Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 471 ◽  
Author(s):  
Arooj Adeel ◽  
Muhammad Akram ◽  
Imran Ahmed ◽  
Kashif Nazar

Linguistic variables play a vital role in several qualitative decision environments, in which decision-makers assume several feasible linguistic values or criteria instead of a single term for an alternative or variable. The motivation for the use of words or sentences instead of numbers is that linguistic classification and characterizations are generally less precise than numerical ones. In this research article, we encourage the fuzzy linguistic approach and introduce the novel concept known as m-polar fuzzy linguistic variable (mFLV) to increase the affluence of linguistic variables based on m-polar fuzzy (mF) approach. An mF set is an effective concept for interpreting uncertainty and fuzziness. The concept of mFLV is more versatile and sensible for dealing with real-life problems, when data comes from qualitative and multipolar information. We also introduce an mF linguistic ELECTRE-I approach to solve multiple-criteria decision-making (MCDM) and multiple-criteria group decision-making (MCGDM) problems, where the evaluation of the alternatives under suitable linguistic values are determined by the decision-makers. Furthermore, we validate the efficiency of our proposed technique by applying it to real-life examples, such as the salary analysis of companies and by selecting a corrupt country. Finally, we develop an algorithm of our proposed approach, present its flow chart, and generate computer programming code.


Author(s):  
Shankha Shubhra Goswami ◽  
Dhiren Kumar Behera

The main objective of this research article is to select the best laptop model among six models available in the market. For this analysis, six laptop models are selected from different online shopping websites having different specifications after seeing the customer ratings. After doing some research, it is found that these laptop models are presently in demand and mostly preferred by the customers. So, an initiative is taken to propose the best laptop among these six models by implementing multiple-criteria decision-making (MCDM) methodology. The selection process is done based on seven criteria (i.e., processor, hard disk capacity, operating system, RAM, screen size, brand, color). For this purpose, analytic hierarchy process (AHP) is adopted for calculating the weightages of the criteria, and TOPSIS is used for selecting the best model. A preference ranking order of the six models is also proposed at the end indicating the best model to the worst. From the whole analysis, it is found that Model 4 came out to be the best model followed by Model 5 and Model 3.


Symmetry ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 295 ◽  
Author(s):  
Rui Wang ◽  
Yanlai Li

To address the complex multiple criteria decision-making (MCDM) problems in practice, this article proposes the picture hesitant fuzzy set (PHFS) theory based on the picture fuzzy set and the hesitant fuzzy set. First, the concept of PHFS is put forward, and its operations are presented, simultaneously. Second, the generalized picture hesitant fuzzy weighted aggregation operators are developed, and some theorems and reduced operators of them are discussed. Third, the generalized picture hesitant fuzzy prioritized weighted aggregation operators are put forward to solve the MCDM problems that the related criteria are at different priorities. Fourth, two novel MCDM methods combined with the proposed operators are constructed to determine the best alternative in real life. Finally, two numerical examples and an application of web service selection are investigated to illustrate the effectiveness of the proposed methods. The sensitivity analysis shows that the different values of the parameter λ affect the ranking of alternatives, and the proposed operators are compared with several existing MCDM methods to illustrate their advantages.


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.


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