https://doi.org/10.1016/j.scs.2022.103669

Adapting Urban Transport Planning to the COVID-19 Pandemic: An Integrated Fermatean Fuzzy Model

The T-Spherical Fuzzy set (T-SPHFS) is one of the core simplifications of quite a lot of fuzzy concepts such as fuzzy set (FS), intuitionistic fuzzy set (ITFS), picture fuzzy set (PIFS), Q-rung orthopair fuzzy set (Q-RUOFS), etc. T-SPHFS reveals fuzzy judgment by the degree of positive membership, degree of abstinence, degree of negative membership, and degree of refusal with relaxed conditions, and this is a more powerful mathematical tool to pair with inconsistent, indecisive, and indistinguishable information. In this article, several novel operational laws for T-SPFNs based on the Schweizer–Sklar t-norm (SSTN) and the Schweizer–Sklar t-conorm (SSTCN) are initiated, and some desirable characteristics of these operational laws are investigated. Further, maintaining the dominance of the power aggregation (POA) operators that confiscate the ramifications of the inappropriate data and Heronian mean (HEM) operators that consider the interrelationship among the input information being aggregated, we intend to focus on the T-Spherical fuzzy Schweizer–Sklar power Heronian mean (T-SPHFSSPHEM) operator, the T-Spherical fuzzy Schweizer–Sklar power geometric Heronian mean (T-SPHFSSPGHEM) operator, the T-Spherical fuzzy Schweizer–Sklar power weighted Heronian mean (T-SPHFSSPWHEM) operator, the T-Spherical fuzzy Schweizer–Sklar power weighted geometric Heronian mean (T-SPHFSSPWGHEM) operator, and their core properties and exceptional cases in connection with the parameters. Additionally, deployed on these newly initiated aggregation operators (AOs), a novel multiple attribute decision making (MADM) model is proposed. Then, the initiated model is applied to the City of Penticton (British Columbia, Canada) to select the best choice among the accessible seven water reuse choices to manifest the practicality and potency of the preferred model and a comparison with the proffered models is also particularized.

https://www.mdpi.com/2071-1050/13/13/7108/pdf

A Novel Approached Based on T-Spherical Fuzzy Schweizer-Sklar Power Heronian Mean Operator for Evaluating Water Reuse Applications under Uncertainty

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.

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

To increase the level of safety and prevent significant accidents, it is essential to prioritize risk factors and assess railway infrastructure. The key question is how to identify unsafe railway infrastructure so authorities can undertake safety improvement projects on time. The paper aims to introduce a picture fuzzy group multi-criteria decision-making approach for risk assessment of railway infrastructure. Firstly, picture fuzzy sets are employed for representing and handling risk-related information. Secondly, a picture fuzzy hybrid method based on the direct rating, and Tsallis–Havrda–Charvat entropy is provided to prioritize risk factors. Thirdly, a picture fuzzy measurement of alternatives and ranking according to compromise solution method is developed to rank railway infrastructures. Lastly, the formulated approach is implemented in the Czech Republic context. Two sensitivity analyses verified the high robustness of the formulated approach. The comparative analysis with five state-of-the-art picture fuzzy approaches approved its high reliability. Compared to the state-of-the-art picture fuzzy approaches, the provided three-parametric approach has superior flexibility.

https://www.mdpi.com/2227-7390/8/12/2259/pdf

Picture Fuzzy MCDM Approach for Risk Assessment of Railway Infrastructure

Circular Economy (CE) is an economic approach which aims to save the environment by eliminating waste and efficiently using resources by applying recycle, reuse, repair, remanufacturing and recycling strategies. The purpose of the article is to propose a concept of measurement the development of Environmental pillar in the context of Circular Economy, apply and provide empirical evidence based on the data of Baltic Sea Region countries. The research augmented for the analysis of Circular Economy which includes assessment model creation. The multi-criteria decision methods MULTIMOORA and TOPSIS were used to assess the development of Environmental pillar of Circular Economy in Baltic Sea Region. Results are useful to add to theoretical building and evaluate the Environmental aspect in the concept of Circular Economy.

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Development of environmental pillar in the context of circular economy assessment: Baltic Sea Region case

Passenger satisfaction is an important factor that affects the choice of travel modes for municipalities, especially in big cities. This evaluation is an important task for managers when they are considering improving the competitiveness of the public transportation system. However, passenger satisfaction evaluation is difficult as the information provided by passengers is often vague, imprecise, and uncertain. This paper aims to propose a new method, using Pythagorean fuzzy sets and multi-objective optimization by a ratio analysis plus full multiplicative form method (MULTIMOORA), to evaluate the passenger satisfaction level of the public transportation system under large group environment. The former is employed to represent the satisfaction assessments of rail transit network provided by passengers. The latter is extended and used to determine the passenger satisfaction levels of rail transit lines. In addition, a combination weighting method is suggested to compute the relative weights of evaluation criteria. A case study of the rail transit network in Shanghai is provided to demonstrate the effectiveness of the proposed passenger satisfaction evaluation method. The result shows that the new method proposed in this study can not only model passengers’ satisfaction evaluation information with more uncertainties, but also determine more reasonable and credible satisfaction levels of rail transit lines.

Hu-Chen Liu

Papers

Passenger Satisfaction Evaluation of Public Transportation Using Pythagorean Fuzzy MULTIMOORA Method under Large Group Environment