A general approach to fuzzy TOPSIS based on the concept of fuzzy multicriteria acceptability analysis

Yatsalo, Boris; Korobov, Alexander; Öztayşi, Başar; Kahraman, Cengiz; Martínez, Luis

doi:10.3233/jifs-179463

Cited by 20 publications

(2 citation statements)

References 60 publications

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“…Among the different multi-criteria decision-making methods that incorporate fuzzy variables, the FTOPSIS method developed by Hwang and Yoon (1981) is considered one of the most widely used (Yatsalo et al, 2020). Its importance lies in the fact that it allows optimising decision making to rank performance by similarity to the ideal solution (ranking method) as collaborative decision makers (Parida, 2020).…”

Section: Ftopsis Methodsmentioning

confidence: 99%

Understanding the dynamics of college transitions between courses: Uncertainty associated with the decision to drop out studies among first and second year students

2023

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University dropout is a phenomenon of growing interest due to its negative consequences. Various variables have been studied in order to understand why this problem occurs. Satisfaction with the degree choice, self-regulation strategies and engagement within the university are some of the variables that have been studied in order to understand why students decide to drop out university. In this sense, it is also important to consider uncertainty, which refers to the level of certainty that students have about these variables to understand the decisions to drop out. Therefore, the aim of this research is to analyse the uncertainty associated with the decision to drop out studies among first year and second-year students, based on these three variables using Multiple Criteria Decision-Making. We performed descriptive analyses and FTOPSIS method on a sample of 719 students from a university in the north of Spain. We saw a relationship between the three variables studied and the intention to persist, as well as being a first-year student. In conclusion, it is important to continue studying the variables that influence this phenomenon in greater depth. In addition, this type of analysis could help in future research to understand in greater depth the influence of other variables on dropout rates.

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Section: Ftopsis Methodsmentioning

confidence: 99%

Understanding the dynamics of college transitions between courses: Uncertainty associated with the decision to drop out studies among first and second year students

2023

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“…Recently, Wu et al [32] proposed a method based on TOPSIS and MCS for the classification of rock masses under uncertainty, while Yatsalo et al [33] introduced a novel fuzzy extension of the TOPSIS method and implemented the Fuzzy Multi-criteria Acceptability Analysis (FMAA) concept within it, while they used MCS to compare the Fuzzy TOPSIS and FMAA models. Moreover, Chen et al [34] proposed a method for evaluating slope stability results based on TOPSIS and Monte Carlo Simulation, and Jun et al [35] ranked alternative scenarios with TOPSIS while introducing a framework for measuring the innovation capacities of financial institutions.…”

Section: Literature Reviewmentioning

confidence: 99%

A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects

et al. 2021

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In this paper, we propose a process that combines the Risk Matrix approach with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Monte Carlo Simulation for assessing risk factors that have an impact on the duration of a construction project’s activities and predict if it is feasible to terminate the project within the prescribed deadlines. Initially, we identified the risks affecting each task of the specific project, and then, we applied the risk matrix approach for determining the probability and impact of every risk to each activity. The resulting ranking is used to assign uncertainty to activities’ durations and estimate the probability of on-time project completion, employing the Monte Carlo Simulation approach. The main contribution of this paper is the development of an innovative framework that coordinates an established qualitative and quantitative risk classification approach, with a popular multicriteria method and a powerful simulation approach, to effectively predict time deviations while executing complex construction projects under uncertainty. The proposed framework was applied to estimate the possibility of a timely execution of an artificial lake real project on the island of Alonissos, Greece. The analysis results illustrate that this approach clearly could help the project risk manager proactively perform risk mitigation measures while allocating budget and programming a project with a significant impact on the quality of life of residents and tourists of a small island.

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Different Approaches to Fuzzy Extension of an MCDA Method and Their Comparison

Yatsalo

Korobov

2020

Advances in Intelligent Systems and Computing

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A general approach to fuzzy TOPSIS based on the concept of fuzzy multicriteria acceptability analysis

Cited by 20 publications

References 60 publications

Understanding the dynamics of college transitions between courses: Uncertainty associated with the decision to drop out studies among first and second year students

Understanding the dynamics of college transitions between courses: Uncertainty associated with the decision to drop out studies among first and second year students

A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects

Different Approaches to Fuzzy Extension of an MCDA Method and Their Comparison

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