Picture Fuzzy MCDM Approach for Risk Assessment of Railway Infrastructure

Šimić, Vladimir; Soušek, Radovan; Jovčić, Stefan

doi:10.3390/math8122259

Cited by 31 publications

(17 citation statements)

References 73 publications

(51 reference statements)

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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%

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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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Section: Literature Reviewmentioning

confidence: 99%

“…The main problems solved in the transport planning area are concerned with railway transport [4,17,26,28,31,35]], transport planning [2,3,9,12,13,24]], railway infrastructure [6,16,23], public transport [1,7,11,30,33], logistics [5,10,20,21,25,27,32,33,36]]. .…”

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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“…This novel extension of fuzzy sets shows superiority in describing decision-maker preferences [34] and mitigating information loss [64]. PFSs are characterized by degrees of positive, neutral, negative, and refusal membership [3,50]. These advanced fuzzy sets are considerably more close to human nature [56].…”

Section: Introductionmentioning

confidence: 99%

Picture fuzzy WASPAS method for selecting last-mile delivery mode: a case study of Belgrade

Šimić

Lazarević

Dobrodolac

2021

Eur. Transp. Res. Rev.

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Background Last-mile delivery (LMD) is becoming more and more demanding due to an increasing number of users and traffic problems in cities. Besides, medical crises (like the COVID-19 outbreak) and air pollution represent additional motives for the transition from traditional to socially and environmentally sustainable LMD mode. An emerging problem for companies in the postal and logistics industry is how to determine the best LMD mode in a multi-criteria setting under uncertainty. Method For the first time, an extension of the Weighted Aggregated Sum Product ASsessment (WASPAS) method under the picture fuzzy environment is presented to solve the LMD mode selection problem. The introduced picture fuzzy set (PFS) based multi-criteria decision-making (MCDM) method can be highly beneficial to managers who are in charge of LMD since it can take into account the neutral/refusal information and efficiently deal with high levels of imprecise, vague, and uncertain information. The comparative analysis with the existing state-of-the-art PFS-based MCDM methods approved the high reliability of the proposed picture fuzzy WASPAS method. Its high robustness and consistency are also confirmed. The presented method can be used to improve LMD in urban areas worldwide. Besides, it can be applied to solve other emerging MCDM problems in an uncertain environment. Findings A real-life case study of Belgrade is presented to fully illustrate the potentials and applicability of the picture fuzzy WASPAS method. The results show that postomates are the best mode for LMD in Belgrade, followed by cargo bicycles, drones, traditional delivery, autonomous vehicles, and tube transport.

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“…Subsequently, fuzzy measurements of alternatives and a compromise solution method were developed to rank railway infrastructures. They demonstrated the substantiality of the proposed approach with sensitivity analyses [30]. In 2020, Marhavilas et al developed a new risk analysis method with the joint collaboration of a deterministic (DET) and a stochastic (STO) process named MCDM-STO/DET for sustainable engineering projects.…”

Section: Introductionmentioning

confidence: 99%

Application of a Novel Hybrid f-SC Risk Analysis Method in the Paint Industry

2021

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Occupational health and safety (OHS) activities aim to ensure the full mental and physical well-being of employees in the workplace. For this reason, it is essential to determine the precautions to be taken and the suitability of risk assessments. In this study, f-SC, a novel hybrid risk analysis method using Step-Wise Weight Assessment Ratio Analysis (SWARA) and Complex Proportional Assessment (COPRAS) multi-criteria decision making methods (MCDM) based on fuzzy logic, was developed to perform a classical Fine–Kinney risk analysis method. There are few studies in the literature about the Fine–Kinney method compared to other risk analysis methods such as FMEA and FTA. Therefore, this work aimed to integrate this classical method with the proposed method to obtain more accurate and sensitive results in risk analyses. First, the criteria used in determining the risk score were weighted with the help of 10 OHS experts. As the criteria used in the classical method are evaluated with equal importance, this situation can cause serious errors in the risk scores obtained with the relevant calculations and in the risk priorities based on these calculations. We aimed to minimize the occurrence of such errors by determining the weights of the criteria with the proposed method. f-SWARA was used for this process. The weights of probability, exposure, and severity criteria were obtained as 0.196, 0.285, and 0.518, respectively. Thus, it was determined that severity is an important and effective criterion for calculating the risk score. In the proposed method, after the criterion weights were determined, an analysis of the hazards was conducted with the f-COPRAS method instead of the classical Fine–Kinney method. Contrary to the numerical values used in the classical method, in this method, decision makers use linguistic terms that are more intuitive than numerical values. These linguistic terms were converted into numerical values using this method based on fuzzy logic, and a ranking of hazards was obtained. As a result of the analyses, it was seen that the case study, H7, which had a 0.557 Ni value, was the most dangerous scenario and that H11, which had a 1.000 Ni value, was the least dangerous. In addition, for the same data, analyses were conducted using the fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, which has been previously used in the literature, and a comparison was made with the f-SC method to demonstrate the validity of the study. The results of the f-VIKOR and classical Fine–Kinney methods were similar to the developed f-SC method. This research provides three contributions: (1) criteria must be weighted to determine risk scores, (2) using intuitive linguistic terms in scoring criteria made the risk analysis method more sensitive and appropriate, and (3) using MCDM methods instead of classical methods for the risk analyses in the OHS field removes uncertainties.

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Picture Fuzzy MCDM Approach for Risk Assessment of Railway Infrastructure

Cited by 31 publications

References 73 publications

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

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

Picture fuzzy WASPAS method for selecting last-mile delivery mode: a case study of Belgrade

Application of a Novel Hybrid f-SC Risk Analysis Method in the Paint Industry

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