2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

The European commission

Preface. Economic Topics. Computable general equilibrium modelling for policy analysis and forecasting (P.B. Dixon, B.R. Parmenter). Computation of equilibria in finite games (R.D. McKelvey, A. McLennan). Computational methods for macroeconomic models (R.C. Fair). Mechanics of forming and estimating dynamic linear economies (E.W. Andersen et al.). Nonlinear pricing and mechanism design (R. Wilson). Sectoral economics (D.A. Kendrick). Computer Science Parallel computation (A. Nagurney). Artificial intelligence in economics and finance: A state of the art - 1994 (L.F. Pau, P.-Y. Tan). Neural networks for encoding and adapting in dynamic economies (I.-K. Cho, T.J. Sargent). Modelling languages in computational economics: GAMS (S.A. Zenios). Numerical Methods. Mathematica for economists (H. Varian). Approximation, perturbation, and projection methods in economic analysis (K.L. Judd). Numerical methods for linear-quadratic models (H.M. Amman). Numerical dynamic programming in economics (J. Rust). Monte Carlo simulation and numerical integration (J. Geweke).

/pdf/handbook-of-computational-economics-531sv06e9a.pdf

Handbook of Computational Economics

The Multiple Criteria Decision Making (MCDM) utility determining approaches and fuzzy sets are considered to be new development approaches, which have been recently presented, extended, and used by some scholars in area of decision making. There is a lack of research regarding to systematic literature review and classification of study about these approaches. Therefore; in the present study, the attempt is made to present a systematic review of methodologies and applications with recent fuzzy developments of two new MCDM utility determining approaches including Step-wise Weight Assessment Ratio Analysis (SWARA) and the Weighted Aggregated Sum Product Assessment (WASPAS) and fuzzy extensions which discussed in recent years. Regarding this, some major databases including Web of Science, Scopus and Google Scholar have been nominated and systematic and meta-analysis method which called “PRISMA” has been proposed. In addition, the selected articles were classified based on authors, the year of publication, journals and conferences names, the technique and method used, research objectives, research gap and problem, solution and modeling, and finally results and findings. The results of this study can assist decision-makers in handling information such as stakeholders’ preferences, interconnected or contradictory criteria and uncertain environments. In addition, findings of this study help to practitioners and academic for adopting the new MCDM utility techniques such as WASPAS and SWARA in different application areas and presenting insight into literature.

A Systematic Review and Meta-Analysis of Swara and Waspas Methods: Theory and Applications with Recent Fuzzy Developments

Application of DEMATEL approach to identify the influential indicators towards sustainable supply chain adoption in the auto components manufacturing sector

Selecting medical treatments is a critical activity in medical decision-making. Usually, medical treatments are selected by doctors, patients, and their families based on various criteria.

/pdf/an-interval-neutrosophic-linguistic-multi-criteria-group-qlcdgra3zh.pdf

An Interval Neutrosophic Linguistic Multi-Criteria Group Decision-Making Method and Its Application in Selecting Medical Treatment Options

In this paper, we introduce L1 metrics in evaluation based on distance from average solution method for multi-criteria decision making. The strength of the proposed modification stems from the following advantages brought by its new distance measures: (1) capability for working with varied statistical data types; (2) increased sensitivity when comparing values of similar magnitudes; and (3) minimized influence of large differences between elements. We also present a variant of this algorithm that is suitable for trapezoidal fuzzy numbers. The merit of the new fuzzy modification is reduced time complexity due to the proposed calculation simplifications. The effectiveness and practicality of these new extensions are illustrated by three data sets for the best alternative selection. The results show that the modifications produce equal or very similar ranking in comparison with original algorithm and other well-known multi-criteria decision-making methods.

Decision analysis with classic and fuzzy EDAS modifications

Despite the worldwide physical closing of educational institutions due to the pandemic of COVID-19 in the spring of 2020, the learning process was not interrupted Learning management systems and digital tools for online collaboration ensured a safe distance and continuity of educational activities However, the rapid transition to remote learning in electronic environment has created a number of challenges in higher education In order to derive longterm benefits from the changes in the way of teaching and examining, the paper explores the possibilities of IoT technology for continuous monitoring and flexible management of the learning process The proposed framework for IoT application in educational activities will facilitate the adaptation of studying process at universities to the new circumstances

/pdf/iot-in-distance-learning-during-the-covid-19-pandemic-2ccj7w7x4c.pdf

IoT in Distance Learning during the COVID-19 Pandemic

Abstract This paper presentsagroup multi-criteria DEMATELand VIKORdecision analysis method with interval type-2 fuzzy sets. In order to compare normal fuzzy trapezoidal numbers, we convert them into crisp values using graded mean integration representation. Byacase study for selection of business intelligence platform, we prove that the proposed combination isafeasible solution that can work with benefits and costs criteria, while also reducing uncertainty in experts’assessments.

/pdf/group-decision-analysis-with-interval-type-2-fuzzy-numbers-2szguss221.pdf

Group Decision Analysis with Interval Type-2 Fuzzy Numbers

The risk of COVID-19 in higher education has affected all its degrees and forms of training. To assess the impact of the pandemic on the learning of university students, a new reference framework for educational data processing was proposed. The framework unifies the steps of analysis of COVID-19 effects on the higher education institutions in different countries and periods of the pandemic. It comprises both classical statistical methods and modern intelligent methods: machine learning, multi-criteria decision making and big data with symmetric and asymmetric information. The new framework has been tested to analyse a dataset collected from a university students’ survey, which was conducted during the second wave of COVID-19 at the end of 2020. The main tasks of this research are as follows: (1) evaluate the attitude and the readiness of students in regard to distance learning during the lockdown; (2) clarify the difficulties, the possible changes and the future expectations from distance learning in the next few months; (3) propose recommendations and measures for improving the higher education environment. After data analysis, the conclusions are drawn and recommendations are made for enhancement of the quality of distance learning of university students.

https://www.mdpi.com/2078-2489/12/4/163/pdf

Effects of COVID-19 Pandemic on University Students’ Learning

/pdf/group-decision-analysis-algorithms-with-edas-for-interval-57ytw3l0a8.pdf

Galina Ilieva

Papers

Decision analysis with classic and fuzzy EDAS modifications

IoT in Distance Learning during the COVID-19 Pandemic

Group Decision Analysis with Interval Type-2 Fuzzy Numbers

Effects of COVID-19 Pandemic on University Students’ Learning

Group Decision Analysis Algorithms with EDAS for Interval Fuzzy Sets