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Öğe Digital Transformation in Automotive Sector(Springer Science and Business Media Deutschland GmbH, 2023) Haktanır, E.; Kahraman, C.; Çebi, S.; Otay, İ.; Boltürk, E.The automotive industry is one of the industries that adapts the fastest to digital transformation (DT) in the world because of its standard production process and mass production. It is the sector that needs digitalization the most in order to gain a competitive advantage and increase its production quality. This chapter focuses on the DT in automotive production processes in both academic literature and industrial applications. It presents the development of automobile technology throughout the years, the type of robots used in automobile production, and an assessment of alternative robot technologies for digital production processes with a sensitivity analysis. The chapter is concluded by future research directions and suggestions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Evaluation of sustainable energy systems in smart cities using a Multi-Expert Pythagorean fuzzy BWM & TOPSIS methodology(Elsevier Ltd, 2024) Otay, İ.; Çevik Onar, S.; Öztayşi, B.; Kahraman, C.Smart cities are technological settlements using the collected data to utilize resources and services effectively by combining information and communication technologies with various tools connected to the internet of things network. Sustainable energy systems in smart cities are systems can be evaluated by using multiple criteria decision making methods or methodologies based on several vague/imprecise evaluation criteria. In this paper, sustainable energy systems in smart cities are evaluated by interval-valued Pythagorean fuzzy (IVPF) sets with an integrated optimization based multi-expert fuzzy Best Worst Method (BWM) and TOPSIS methodology that can better handle uncertainty and vagueness in experts’ linguistic assessments than existing methodologies. The considered criteria are weighted by multi-expert IVPF Best Worst Method, which has become a popular weighting method in recent years. Later, the energy alternatives for a real case study are prioritized by multi-expert IVPF TOPSIS method. In the analysis, the most important criterion is found as Environmental sustainability (C1) with the defuzzified weight of 0.218 while the other weights are as initial investment (C2) with 0.196, operating expenses (C3) with 0.163, technical feasibility (C4) with 0.154, social acceptability (C5) with 0.140, and scalability (C6) with 0.129. The obtained results indicate that “Investing in advanced technologies” in a smart city with relative degree of closeness (RDC) value of 0.798, has been determined as the best alternative among the considered five alternatives. It is closely followed by “Developing a transportation system” with the RDC value of 0.681. Sensitivity analysis shows that the ranking results are quite robust and reliable. The comparative analysis with crisp BWM and TOPSIS methodology is applied to check the validity of the proposed methodology. © 2024 Elsevier LtdÖğe Extension of VIKOR Method Using Circular Intuitionistic Fuzzy Sets(Springer Science and Business Media Deutschland GmbH, 2022) Kahraman, C.; Otay, I.VIKOR method is used to solve a variety of MCDM problems including a variety of criteria that can be conflicting and noncommensurable. This method is based on the distances of alternatives to positive and negative ideal solutions, and provides compromising solutions. Decision makers generally prefer to evaluate the alternatives with respect to the criteria by using linguistic terms rather than assigning exact numerical values. The fuzzy set theory captures the uncertainty and subjectivity in these linguistic terms successfully. Many classical MCDM methods have been extended to their fuzzy versions by using the fuzzy set theory for handling this uncertainty. VIKOR method has been extended by using several fuzzy set extensions such as intuitionistic fuzzy VIKOR, hesitant fuzzy VIKOR, Pythagorean fuzzy VIKOR, picture fuzzy VIKOR, and spherical fuzzy VIKOR methods. Circular intuitionistic fuzzy sets (C-IFS) introduced as an extension of intuitionistic fuzzy sets, enables decision makers to define membership and the non-membership degrees as circular membership functions. In this paper, we develop C-IFS VIKOR method and apply it to a waste disposal location selection problem. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Extensions of Ordinary Fuzzy Sets: A Comparative Literature Review(Springer, 2021) Kahraman, C.; Oztaysi, B.; Otay, I.; Onar, S.C.Fuzzy sets extensions have been often used in the modeling of problems including vagueness and impreciseness in order to better define the membership functions together with the hesitancy of decision makers. More than 20 different extensions of ordinary fuzzy sets have appeared in the literature after the introductions of ordinary fuzzy sets by Zadeh (1965). These sets involve interval-type fuzzy sets, type-2 fuzzy sets, hesitant fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets, q-rung orthopair fuzzy sets, spherical fuzzy sets, picture fuzzy sets, fermatean fuzzy sets, etc. Mainly, these extensions can be divided into two classes: extensions with two independent membership parameters and extensions with three independent membership parameters. In this paper, we briefly classify these extensions and present some comparative graphical illustrations. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Modeling Humanoid Robots Mimics Using Intuitionistic Fuzzy Sets(Springer, 2021) Kahraman, C.; Onar, S.C.; Oztaysi, B.; Otay, I.Intuitionistic fuzzy sets (IFS) have been often used in modeling the problems under vagueness and impreciseness in order to better define the problems together with the hesitancy of decision makers. IFS have been often employed in modeling decision making problems in the literature. Human decision making process can be used in humanoid robots by imitating the human decisions and behaviors. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
