An Integrated Approach of Best-Worst Method (BWM) and Triangular Fuzzy Sets for Evaluating Driver Behavior Factors Related to Road Safety

Moslem, Sarbast; Gül, Muhammet; Farooq, Danish; Çelik, Erkan; Ghorbanzadeh, Omid; Blaschke, Thomas

doi:10.3390/math8030414

Cited by 73 publications

(40 citation statements)

References 71 publications

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“…The multilevels concept is a general structure for the hierarchy. The application was used to evaluate several transportation complex problems [32][33][34][35] The importance of the linkages among the criteria in the different levels are determined by a global score for the criteria in the last level. The main steps of the conventional AHP follow:…”

Section: Overview Of the Conventional Analytic Hierarchy Process (Ahp)mentioning

confidence: 99%

An Integrated Decision Support Model for Evaluating Public Transport Quality

et al. 2020

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Big cities suffer from serious complex problems such as air pollution, congestion, and traffic accidents. Developing public transport quality in such cities is considered an efficient remedy to obviate these critical issues. This paper aims to determine the significant supply quality criteria of public transportation. As a methodology, a hybrid Analytic Hierarchy Process (AHP) combined with the Best Worst Method (BWM) is applied. The proposed model is basically a hierarchy structure with at least a 5 × 5 pairwise comparison matrix or larger. A real-world complex problem was examined to validate the created model (public transport quality improvement). An urban bus transport system in the Jordanian capital city, Amman, was used as a case study; three stakeholder groups (passengers, nonpassengers, and representatives of the local government) participated in the evaluation process. The conventional Analytic Hierarchy Process (AHP) leads to weak consistency in the case of existing 5 × 5 pairwise comparison matrices or larger, particularly in estimating complex problems. To avoid this critical issue in AHP, we used Best Worst Method (BWM) comparisons, which make the evaluation process easier for decision makers; moreover, it saves survey time and provides more consistency when compared to AHP pairwise comparisons. The model adopted highlighted the most significant service quality criteria that influence urban bus transport systems. Furthermore, the sensitivity analysis conducted detected the stability of the criteria ranking in the three levels of the hierarchical structure. Since the proposed AHP–BWM model (which is the sole example of this sort of combination) is independent from the decision attributes, it can be applied to arbitrary hierarchically structured decision problems with a relatively large number of pairwise comparisons.

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Section: Overview Of the Conventional Analytic Hierarchy Process (Ahp)mentioning

confidence: 99%

An Integrated Decision Support Model for Evaluating Public Transport Quality

et al. 2020

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“…It is applied to various fields from manufacturing to service [37]. After its initial development and applying to various areas, it has also been extended methodologically by fuzzy sets [41]. Guo and Zhang [22] developed triangular FBWM and applied it in the logistics industry.…”

Section: Fuzzy Best-worst Methods (Fbwm)mentioning

confidence: 99%

A holistic FMEA approach by fuzzy-based Bayesian network and best–worst method

Yücesan

Gül

Çelik

2021

Complex Intell. Syst.

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Failure mode and effect analysis (FMEA) is a risk analysis tool widely used in the manufacturing industry. However, traditional FMEA has limitations such as the inability to deal with uncertain failure data including subjective evaluations of experts, the absence of weight values of risk parameters, and not considering the conditionality between failure events. In this paper, we propose a holistic FMEA to overcome these limitations. The proposed approach uses the fuzzy best–worst (FBWM) method in weighting three risk parameters of FMEA, which are severity (S), occurrence (O), and detection (D), and to find the preference values of the failure modes according to parameters S and D. On the other side, it uses the fuzzy Bayesian network (FBN) to determine occurrence probabilities of the failure modes. Experts use a procedure using linguistic variables whose corresponding values are expressed in trapezoidal fuzzy numbers, and determine the preference values of the failure modes according to parameter O in the constructed BN. Thus, the FBN including expert judgments and fuzzy set theory addresses uncertainty in failure data and includes a robust probabilistic risk analysis logic to capture the dependence between failure events. As a demonstration of the approach, a case study was conducted in an industrial kitchen equipment manufacturing facility. The results of the approach have also been compared with existed methods demonstrating its robustness.

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“…Table 1 summarizes the available fuzzy MCDM approaches in the transport area. The fuzzy multi-criteria methods can be summarized as follows: pair-wise comparisons [1][2][3][4][5][6][7][8][9]; distance based [10][11][12][13][14][15][16][17][18]; utility based [19][20][21][22][23][24][25][26]; outranking [27,28]; integration of two or more methods [29][30][31][32][33][34][35][36].…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Fuzzy SIMUS Multicriteria Decision-Making Method. An Application in Railway Passenger Transport Planning

Stoilova

Munier

2021

Symmetry

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To increase the level of adequacy in multi-criteria decision-making in the case of uncertainty, it is essential to reduce the subjectivism and to increase the reality of obtained results. The study aims to propose a novel fuzzy multi-criteria method based on the fuzzy linear programming method and sequential interactive model for urban systems method (SIMUS), named fuzzy SIMUS. This paper is something completely different because it links the power of fuzzy with the advantage of the SIMUS method. Indeed, not using weights, it works with optimal values. Here, this procedure is presented for the first time. The methodology consists of three stages. The first stage includes forming the parameters of a multi-criteria model in the case of uncertainty. The initial matrix has three values: lower, medium, and upper. In the second stage, the fuzzy SIMUS model for each objective is formed based on fuzzy linear programming method. The third stage deals with the ranking of the alternatives. The methodology was experimented for planning railway intercity passenger transport in Bulgarian’s railway network. Nine alternative transport plans and eight criteria were studied. It was found that the objectives which influence ranking the most are the frequency of train stops (15%), direct operational costs (15%), train’s capacity (14.7%), and reliability (14.3%). A transport plan for railway passenger transport is proposed. A verification of the results was performed. It was found that the stability of the choice presented a suitable alternative.

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An Integrated Approach of Best-Worst Method (BWM) and Triangular Fuzzy Sets for Evaluating Driver Behavior Factors Related to Road Safety

Cited by 73 publications

References 71 publications

An Integrated Decision Support Model for Evaluating Public Transport Quality

An Integrated Decision Support Model for Evaluating Public Transport Quality

A holistic FMEA approach by fuzzy-based Bayesian network and best–worst method

A Novel Fuzzy SIMUS Multicriteria Decision-Making Method. An Application in Railway Passenger Transport Planning

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