Evaluation of life quality by integrated method of AHP and TOPSIS based on interval type-2 fuzzy sets

Şahin, Aynur; Pehlivan, Nimet Yapıcı

doi:10.15672/hjms.2017.420

Cited by 8 publications

(7 citation statements)

References 32 publications

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“…It is based on selection of alternative which has the shortest distance from the positive-ideal solution and the farthest distance from the negative-ideal solution. The steps of the TOPSIS method for a MCDM problem involving m alternatives and n criteria as follows (Chen, 2000;Opricovic and Tzeng, 2004;Şahin and Pehlivan, 2017):…”

Section: Topsis Methodsmentioning

confidence: 99%

Gamma Dağılımının Parametrelerinin Tahmini için Metasezgisel Yöntemlerin Değerlendirilmesi ve Karşılaştırılması

Yonar

Pehlivan

2022

Nicel Bilimler Dergisi

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Parameter estimation of three parameter (3-p) Gamma distribution is very important as it is one of the most popular distributions used to model skewed data. Maximum Likelihood (ML) method based on finding estimators that maximize the likelihood function, is a well-known parameter estimation method. It is rather difficult to maximize the likelihood function formed for the parameter estimation of the 3-p Gamma distribution. In this study, five well known metaheuristic methods, Simulated Annealing (SA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), and Artificial Bee Colony (ABC), are suggested to obtain ML estimates of the parameters for the 3-p Gamma distribution. Monte-Carlo simulations are performed to examine efficiencies of the metaheuristic methods for the parameter estimation problem of the 3-p Gamma distribution. Also, differences between solution qualities and computation time of the algorithms are investigated by statistical tests. Moreover, one of the multi-criteria decision-making methods, Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), is preferred for ranking the metaheuristic algorithms according to their performance in parameter estimation. Results show that Differential Evolution is superior to the others for this problem in consideration of all the criteria of solution quality, computation time, simplicity, and robustness of the metaheuristic algorithms. In addition, an analysis of real-life data is presented to demonstrate the implementation of the suggested metaheuristic methods.

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Section: Topsis Methodsmentioning

confidence: 99%

Gamma Dağılımının Parametrelerinin Tahmini için Metasezgisel Yöntemlerin Değerlendirilmesi ve Karşılaştırılması

Yonar

Pehlivan

2022

Nicel Bilimler Dergisi

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“…Kahraman et al (2014) introduced IT2F AHP as an extension of type-1 fuzzy AHP. The IT2F-based AHP was used for different implementation purposes (Sahin and Yapici Pehlivan, 2017; Kaya and Aycin, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

A novel belief-based QFD-AHP model in interval type-2 fuzzy environment for lean after-sales service in automotive industry

Başkır

2023

IJLSS

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Purpose The purpose of this paper is to propose a novel lean management tool to provide a comprehensive and flexible evaluation model while converting customer voices into technical characteristics in lean implementations. Design/methodology/approach For this purpose, the proposed model was constructed by belief space-evaluations, quality function deployment (QFD) and analytic hierarchy process (AHP) in interval type-2 fuzzy (IT2F) environment. This model involves three phases: determining the linguistic weights and belief-based relations with their IT2F-sets, processing information about IT2F-based belief-evaluations and ranking the technical characteristics using the defuzzified belief-based relative importance values. Findings The proposed model was applied to automotive after-sales service in Turkey to demonstrate its use in lean service-decisions. This model was compared with its classical and type-1 fuzzy versions. The ranking-results of the proposed model differed from those of the other versions. The reason is that the IT2F-environment offers a sensitive and flexible evaluation of the model’s linguistic scales. Research limitations/implications Calculations in the proposed model may be quite involved for practitioners. An Excel-dashboard was created to simplify the computational complexity. Practical implications Researchers/practitioners can apply this model to any lean manufacturing/service implementation. Social implications Company managers/employees/customers can recognize their perception-mechanisms via belief space-evaluations and experience how uncertainty in the perception-mechanism affects their decisions. Originality/value The proposed model provides a new lean tool due to the Bayesian model combined with QFD-AHP in IT2F-environment. This model eliminates the ambiguity in conceptual change-based lean decisions.

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“…Moving to the third phase, alternatives were evaluated by constructing the fuzzy decision matrices using linguistic terms and the weighted matrices. Subsequently, the fuzzy ideal positive and negative solutions are calculated and compared with the relative closeness rations of the alternatives [22].…”

Section: Hybrid Fuzzy Mcdm Techniques and General Applicationmentioning

confidence: 99%

“…On the other side, the alternatives are compared using the TOPSIS method and the result is integrated with the AHP results in the decision matrix. Furthermore, the ideal negative and positive solutions were calculated, and the alternatives' relative closeness is calculated in order to rank them [22].…”

Section: Model Designmentioning

confidence: 99%

Development of Decision Support Model for Selecting a Maintenance Plan Using a Fuzzy MCDM Approach: A Theoretical Framework

Abdulgader

Eid

Rouyendegh

2018

Applied Computational Intelligence and Soft Computing

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In complex decision making, using multicriteria decision-making (MCDM) methodologies is the most scientific way to ensure an informed and justified decision between several alternatives. MCDMs have been used in different ways and with several applications that proved their efficiency in achieving this goal. In this research, the advantages and disadvantages of the different MCDM methodologies are studied, along with the different techniques implemented to increase their accuracy and precision. The main aim of the study is to develop a hybrid MCDM process that combines the strengths of several MCDM methods and apply it to choose the best fit maintenance policy/strategy for industrial application. Moreover, fuzzy linguistic terms are utilized in all of the used MCDM techniques in order to eliminate the uncertainty and ambiguity of the results. Through an extensive literature review performed on studies that have used MCDM methods in a hybrid context and using fuzzy linguistic terms, a model is developed to use fuzzy DEMATEL-AHP-TOPSIS hybrid technique. The model with its application is the first of its kind, which combines the strengths of fuzzy DEMATEL in establishing interrelationships between several criteria, as well as performing a pairwise comparison between the criteria for prioritization using the fuzzy AHP method. Thereafter, the alternatives are compared using fuzzy TOPSIS method by establishing negative and positive solutions and calculating the relative closeness for each of the alternatives. Furthermore, six main criteria, twenty criteria, and five alternatives are selected from the literature for the model application.

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Evaluation of life quality by integrated method of AHP and TOPSIS based on interval type-2 fuzzy sets

Cited by 8 publications

References 32 publications

Gamma Dağılımının Parametrelerinin Tahmini için Metasezgisel Yöntemlerin Değerlendirilmesi ve Karşılaştırılması

Gamma Dağılımının Parametrelerinin Tahmini için Metasezgisel Yöntemlerin Değerlendirilmesi ve Karşılaştırılması

A novel belief-based QFD-AHP model in interval type-2 fuzzy environment for lean after-sales service in automotive industry

Development of Decision Support Model for Selecting a Maintenance Plan Using a Fuzzy MCDM Approach: A Theoretical Framework

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