Mühendislik Fakültesi / Faculty of Engineering
Permanent URI for this collectionhttps://hdl.handle.net/11727/1401
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Item A New Hybrid Intuitionistic Approach for New Product Selection(2018) Atalay, Kumru Didem; Can, Gulin FeryalThis paper proposes a new hybrid approach for multi-criteria decision-making problems combining intuitionistic fuzzy analytic hierarchy process and intuitionistic fuzzy multi-objective optimization by ratio analysis. Analytic hierarchy process has an inherent ability for handling intangible problems and implements a simple scale to represent evaluations in the structure of pairwise comparisons. Multi-objective optimization by ratio analysis optimizes the solution of a problem having two or more conflicting objectives, taking into account certain constraints. In real-life decision problems, evaluations of decision makers related to performance of alternatives and criteria weights can be expressed by linguistic terms comprising vagueness and uncertainty. These uncertain, vague and hesitant judgments of decision makers can be described more comprehensively by using intuitionistic fuzzy set theory. The proposed approach is a powerful tool for dealing with information which consists of hesitancy and vagueness. An illustrative example related to new product selection for a company is also presented to demonstrate the implementation of the approach.Item A Case Study on Shopping Malls Attributes for Young Consumers(2016) Can, Gulin Feryal; Kurtulmusoglu, Feride Bahar; Atalay, Kumru DidemPurpose - This study aims to determine the mall criteria that are the most crucial for the youth market by determining the winning brand in comparison to other offerings to understand what is required to gain a competitive advantage and to differentiate a mall from its rivals. Design/methodology/approach - This study chose the Stochastic Multicriteria Acceptability Analysis-2 method to evaluate the mall preferences of young people. By using this method, the various criteria were evaluated for more than one alternative to find the best solution. JSMA program was used to analyze the data. The survey was administered using the mall intercept method to reduce sample bias. Findings - The study identifies that the criteria that have the highest impact on the mall preferences of young people are the mall campaigns for loyal customers; the traffic in the mall locality and the mall's parking facilities; the mall's facilities for disabled people; the quality of the mall locality; and the quality of the people visiting the mall. The study reveals that a mall's physical features, its facilities and the criteria related to employees have a very low impact on the mall choices of young people. The study further finds that the youth market has very low satisfaction levels for all of the identified criteria. This study reveals that this macro accessibility criterion is less relevant for the youth market than for the general population. Originality/value - Despite the importance of this market, there is insufficient research on the shopping behavior of young people. They have a considerable impact on the purchasing decisions of their families, significant disposable income and constitute the future market for the sector. This study uniquely enables the sequential ordering of customers' decision-making criteria and determines the effectiveness or impact of these criteria in the mall sector.Item Evaluation of Effect of Different Membership Functions on Risk Assessment(2018) Atalay, Kumru Didem; Can, Guelin Feryal; Eraslan, Ergun; 28330411This study aims to define the relationship between risk degrees and risk indexes on different functional structures with the assumption that risk degrees may not always present a linear relationship with the risk indexes. In this way, risk indexes suitable for expert evaluation of working conditions and computed using three different membership functions are determined. Among the membership functions used, one is preferred as linear and the others are preferred as non-linear. Additionally, a new fuzzy risk assessment (RA) algorithm is developed using these three membership functions. With this new fuzzy RA algorithm, a more flexible and precise process becomes available, while information loss during the determination of the risk index of danger sources is prevented. As a result, non-linear increasing membership function is selected as most suitable for the expression of the relationship between risk degrees and risk indexes.Item A New Stochastic MCDM Approach Based on COPRAS(2018) Ayrim, Yelda; Atalay, Kumru Didem; Can, Gulin FeryalThis study proposes a novel integrated Complex Proportional Assessment (COPRAS) approach by using stochastic decision process named as Stochastic COPRAS (COPRAS-S) to increase the evaluation performance of COPRAS. In COPRAS-S, criteria importance weights and the performance values of alternatives are determined by generating random numbers from uniform distribution in a range of minimum and maximum values of a limited number of decision-maker evaluations. Thus, the numbers of experts are increased and decision-making process is performed in an effective way because different opinions are incorporated. In addition, randomness feature brought with vagueness in decision is modeled in this process. A special normalization approach based on standard deviation is also implemented in COPRAS-S. In this way, cost and benefit type criteria are evaluated in a different way. This proposed stochastic structure for COPRAS is a practical and powerful tool that strengthens the decision.Item Development of a Decision Support System for Selection of Reviewers to Evaluate Research and Development Projects(2023) Kocak, Serdar; Ic, Yusuf Tansel; Sert, Mustafa; Atalay, Kumru Didem; Dengiz, BernaThe evaluation of Research and Development (R&D) projects consists of many steps depending on the government funding agencies and the support program. It is observed that the reviewer evaluation reports have a crucial impact on the support decisions of the projects. In this study, a decision support system (DSS), namely R&D Reviewer, is developed to help the decision-makers with the assignment of the appropriate reviewer to R&D project proposals. It is aimed to create an artificial intelligence-based decision support system that enables the classification of Turkish R&D projects with natural language processing (NLP) methods. Furthermore, we examine the reviewer ranking process by using fuzzy multi-criteria decision-making methods. The data in the database is processed primarily to classify the R&D projects and the word embedding model NLP, "Word2Vec". Also, we designed the Convolutional Neural Network (CNN) model to select the features by using the automatic feature learning approach. Moreover, we incorporate a new integrated hesitant fuzzy VIKOR and TOPSIS methodology into the developed DSS for the reviewer ranking process.Item A new hybrid method to determine the hazardous risk factors(2022) Dinler, Esra; Atalay, Kumru Didem; Guler, EzgiIn risk analysis, the quantification of risk, the modeling of identified risk, and how to make decisions are all topics considered. Risk analysis activity that companies must comply with and perform at a minimum level to produce medical devices. Manufacturers should consider all risks that the device may contain to indicate that the medical device is safe. Manufacturers must also justify that this device should be manufactured because the benefit of the device is greater than the risk. This study proposes a method to measure the risk factors of the medical devices on the patient. Accordingly, a mathematical model is developed, the model is applied to a device manufactured in a company, and the results are obtained. The aggregated method developed in this study, based on the Taguchi loss function and using the hesitant fuzzy the technique for order preference by similarity to ideal solution (HF-TOPSIS) method, ensures that the risks that may occur for the patient are minimized and the risk types to be taken into account are determined. In addition, the order of importance of the risk types obtained with the proposed method in the study is compared with the TOPSIS method.Item The development of a reviewer selection method: a multi-level hesitant fuzzy VIKOR and TOPSIS approaches(2021) Kocak, Serdar; Ic, Yusuf Tansel; Atalay, Kumru Didem; Sert, Mustafa; Dengiz, Berna; 0000-0001-9274-7467; AGE-3003-2022This paper proposes a new approach for the selection of reviewers to evaluate research and development (R&D) projects using a new integrated hesitant fuzzy VIKOR and TOPSIS methodology. A reviewer selection model must have a multi-level framework in which reviewer selection strategies and related objectives guide the second level of the reviewer performance ranking process. The model must measure reviewer performance related to the activities that are necessary for the R&D project evaluation to be successful. A novel model is presented in this paper. In the proposed methodology, the aim is to select a reviewer in a hierarchical decision-making structure. The selection criteria values and their weights were obtained using the hesitant fuzzy VIKOR method. For the selection of a suitable reviewer, the conventional TOPSIS model was used. We developed a simpler procedure for effectively performing the reviewer selection process. The new approach was tested with a real case study and satisfactory results were obtained. A comparative analysis is also included in the article for illustrative purposes.Item Development of a new hesitant fuzzy ranking model for NTMP ranking problem(2021) Atalay, Kumru Didem; Ic, Yusuf Tansel; Kececi, Baris; 0000-0001-9274-7467; AGE-3003-2022Nontraditional manufacturing processes (NTMPs) bring the processing capabilities such as machining high strength and hard materials with desired accuracies and surface finish to the manufacturing companies. Therefore, there has been a significant increase in the use and number of NTMPs. Hence, choosing a particular NTMP for a specific application turns out to be a complex decision-making problem, which involves conflicting qualitative and quantitative ranking criteria. In recent NTMP ranking literature, it is noted that fuzzy approaches are better suited for handling uncertainties and incomplete information that exist within the NTMP ranking environment. This paper introduces such a fuzzy approach using the hesitant fuzzy preference selection index (PSI) method for the assessment of the criteria weights and the hesitant fuzzy correlation coefficient principle for ranking and recommending the most appropriate NTMP for a specific application. The proposed methodology and its efficiency in dealing with incomplete information under the fuzzy decision-making environment are explored with a case study. As a result of the study, the proposed model preferred the electron beam machining (EBM) as the most suitable nontraditional manufacturing process. On the other hand, triangular fuzzy TOPSIS methods offered the electrochemical machining (ECM) as the best choice among the alternatives. The differences among the ranking decisions are also analyzed in the paper. It can be concluded from the authors' various applications of the proposed hesitant fuzzy PSI method that it is extremely effective in representing fuzzy decision-making environments in NTMP ranking decisions.Item A New Methodology for Solving Multiobjective Chance-Constrained Problems: An Application on IoT Systems(2021) Atalay, Kumru Didem; Pekin, Tacettin Sercan; Apaydin, Aysen; 0000-0002-9021-3565This study presents a newly developed methodology to transform the chance-constrained problem into a deterministic problem and then solving this multiobjective deterministic problem with the proposed method. Chance-constrained problem contains independent gamma random variables that are denoted as a(ij). Two methods are proposed to obtain the deterministic equivalent of chance-constrained problem. The first of the methods is directly based on using the distribution, and the second consists of normalizing probabilistic constraints using Lyapunov's central limit theorem. An algorithm which uses the Global Criterion Method is developed to solve the multiobjective deterministic equivalent of chance-constrained problem. The methodology is applied to a real-life engineering problem that consists of an IoT device and its data sending process. Using Lyapunov's central limit theorem for large numbers of random variables is found to be more appropriate.Item Airfoil-slat arrangement model design for wind turbines in fuzzy environment(2020) Atalay, Kumru Didem; Dengiz, Berna; Yavuz, Tahir; Koc, Emre; Ic, Yusuf TanselIn this study, a multi-element wind turbine blade that consists of NACA 6411 and NACA 4412 leading-edge slat design is investigated computationally. Optimum design parameters of the slatted wind turbine blade leading to maximum value of C-L/C-D related to the turbine power are obtained. In the optimization process, a new fuzzy logic linear programming methodology integrating with fuzzy linear regression and 2D CFD analysis is proposed. The aerodynamic characteristics of the slatted blade are computed by using Incompressible Navier-Stokes equations and k-omega turbulence modeling. Results are compared with the results of linear programming method and direct search optimization method. The computational results reveal that the proposed methodology for performance optimization is more effective than other methods to obtain high-performance value of the C-L/C-D. The maximum value of the C-L/C-D is obtained as 25.1 leading the maximum efficiency of 0.52.