Endüstri Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1942

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Now showing 1 - 7 of 7

Citation - Scopus: 8
Analysis of Intelligent Software Implementations in Air Cargo Using Fermatean Fuzzy Codas Method
(Springer, 2022) Sergi, Duygu; Sarı, İrem Ucal; Kuchta, Dorota
The chapter focuses on the problem of analyzing and selecting intelligent software in Air Cargo in the concept of Aviation 4.0. First, the notions, problems and challenges linked to air cargo are discussed. Recent developments, ongoing innovative projects and unfilled gaps in the area of intelligent air cargo software are presented. Next, the proposed method to analyze a select software to be used by air cargo companies is described. It is a modified version of one of the recent multi-criteria decision-making methods, called CODAS. Its original, crisp version and its existing fuzzy extensions are first presented. Next, an original extension of the method, using Fermatean fuzzy sets, is proposed. In the application section a logistics company is considered, which is facing the problem of selecting software supporting the air cargo process. The criteria are selected by experts holding various positions in the company, and three alternatives of air cargo software provider are determined. Then, the proposed method is applied to solve the intelligent software selection problem. Finally, conclusion and future research perspectives are given.
Citation - WoS: 12
Citation - Scopus: 12
Bilevel Models on the Competitive Facility Location Problem
(Springer, 2017) Küçükaydın, Hande; Aras, Necati
Facility location and allocation problems have been a major area of research for decades, which has led to a vast and still growing literature. Although there are many variants of these problems, there exist two common features: finding the best locations for one or more facilities and allocating demand points to these facilities. A considerable number of studies assume a monopolistic viewpoint and formulate a mathematical model to optimize an objective function of a single decision maker. In contrast, competitive facility location (CFL) problem is based on the premise that there exist competition in the market among different firms. When one of the competing firms acts as the leader and the other firm, called the follower, reacts to the decision of the leader, a sequential-entry CFL problem is obtained, which gives rise to a Stackelberg type of game between two players. A successful and widely applied framework to formulate this type of CFL problems is bilevel programming (BP). In this chapter, the literature on BP models for CFL problems is reviewed, existing works are categorized with respect to defined criteria, and information is provided for each work.
Citation - Scopus: 27
Fuzzy Capital Budgeting Using Fermatean Fuzzy Sets
(Springer, 2021) Sergi, Duygu; Sarı, İrem Ucal
Investment projects are mostly evaluated by capital budgeting techniques to measure their profitability. The parameters used in capital budgeting such as future cash flows, interest rate and useful life involves high uncertainty due to the lack of information for the future environment. Since the uncertainty involved in forecasting the parameters is mostly in high levels, fuzzy set theory could be used in the determination of capital budgeting parameters to handle uncertain information in the analyses. Fermatean fuzzy sets are one of the most recent extensions of fuzzy set theory which are capable to handle higher levels of uncertainties by assigning fuzzy parameters from a larger domain. In this paper, fuzzy capital budgeting techniques that are fuzzy net present worth, fuzzy net future worth and fuzzy net annual worth are extended using fermatean fuzzy sets. An illustration for the calculations is also presented.
Citation - Scopus: 1
Interval Valued Intuitionistic Fuzzy Z Extensions of Ahp&codas: Comparison of Energy Storage Alternatives
(Springer, 2023) Sergi, Duygu; Sarı, İrem Uçal
Energy storage technologies are receiving increasing attention due to the trend toward renewable energy sources. Energy storage systems are a promising technology as they provide the low carbon emissions needed in the future, contribute to renewable energy production, and offer an alternative to petroleum-derived fuels. It is not possible to say precisely how the energy will be stored, and often more than one method must be used together. In this study, battery technologies from electrochemical energy storage systems are discussed. This chapter proposes a multi-criteria decision-making (MCDM) model combining fuzzy IVIF-Z-AHP and fuzzy IVIF-Z-CODAS methods to choose the optimal battery ESS. The priority weights of 4 main and 11 sub-criteria related to energy storage efficiency are determined using the IVIF-Z-AHP method. After that, 5 different batteries are evaluated using the IVIF-Z-CODAS method, and the most appropriate battery ESS is selected by doing a performance evaluation regarding the storage of energy at maximum efficiency.
Citation - WoS: 5
Citation - Scopus: 9
Predicting Cash Holdings Using Supervised Machine Learning Algorithms
(Springer, 2022) Özlem, Şirin; Tan, Ömer Faruk
This study predicts the cash holdings policy of Turkish firms, given the 20 selected features with machine learning algorithm methods. 211 listed firms in the Borsa Istanbul are analyzed over the period between 2006 and 2019. Multiple linear regression (MLR), k-nearest neighbors (KNN), support vector regression (SVR), decision trees (DT), extreme gradient boosting algorithm (XGBoost) and multi-layer neural networks (MLNN) are used for prediction. Results reveal that MLR, KNN, and SVR provide high root mean square error (RMSE) and low R2 values. Meanwhile, more complex algorithms, such as DT and especially XGBoost, derive higher accuracy with a 0.73 R2 value. Therefore, using advanced machine learning algorithms, we may predict cash holdings considerably.
Citation - WoS: 30
Citation - Scopus: 36
Prioritization of Public Services for Digitalization Using Fuzzy Z-Ahp and Fuzzy Z-Waspas
(Springer, 2021) Ucal Sarı, İrem; Sergi, Duygu
In this paper, public services are analyzed for implementations of Industry 4.0 tools to satisfy citizen expectations. To be able to prioritize public services for digitalization, fuzzy Z-AHP and fuzzy Z-WASPAS are used in the analysis. The decision criteria are determined as reduced cost, fast response, ease of accessibility, reduced service times, increase in the available information and increased quality. After obtaining criteria weights using fuzzy Z-AHP, health care services, waste disposal department, public transportation, information services, social care services, and citizen complaints resolution centers are compared using fuzzy Z-WASPAS that is proposed for the first time in this paper. Results show that health care services have dominant importance for the digitalization among public services.
Citation - Scopus: 3
Selection of the Best Face Recognition System for Check in and Boarding Services
(Springer, 2022) Ucal Sarı, İrem; Sergi, Duygu; Kuchta, Dorota
Check-in and boarding services are one of the most human oriented pre-flight services in aviation industry. The process of using face recognition systems increase with the aviation 4.0 concept, decreases need for manpower and increases the efficiency of the processes. Therefore, problems, developments and challenges of face recognition in terms of aviation 4.0 are discussed in this chapter to determine the best face recognition system for check in and boarding systems. Analytic hierarchy process and grey relational analysis are used to analyze current system providers. To handle the ambiguity in the linguistic evaluations, fuzzy Z- numbers are used. 10 face recognition system providers are evaluated according to five criteria with the proposed methodology and the results are discussed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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