Browsing by Author "Kucukonder, Hande"

Now showing 1 - 19 of 19

Citation Count: 2
3D Printer Selection for the Sustainable Manufacturing Industry Using an Integrated Decision-Making Model Based on Dombi Operators in the Fermatean Fuzzy Environment
(Mdpi, 2024) Görçün, Ömer Faruk; Zolfani, Sarfaraz Hashemkhani; Kucukonder, Hande; Antucheviciene, Jurgita; Pavlovskis, Miroslavas
Three-dimensional printers (3DPs), as critical parts of additive manufacturing (AM), are state-of-the-art technologies that can help practitioners with digital transformation in production processes. Three-dimensional printer performance mostly depends on good integration with artificial intelligence (AI) to outperform humans in overcoming complex tasks using 3DPs equipped with AI technology, particularly in producing an object with no smooth surface and a standard geometric shape. Hence, 3DPs also provide an opportunity to improve engineering applications in manufacturing processes. As a result, AM can create more sustainable production systems, protect the environment, and reduce external costs arising from industries' production activities. Nonetheless, practitioners do not have sufficient willingness since this kind of transformation in production processes is a crucial and irrevocable decision requiring vast knowledge and experience. Thus, presenting a methodological frame and a roadmap may help decision-makers take more responsibility for accelerating the digital transformation of production processes. The current study aims to fill the literature's critical theoretical and managerial gaps. Therefore, it suggests a powerful and efficient decision model for solving 3DP selection problems for industries. The suggested hybrid FF model combines the Fermatean Fuzzy Stepwise Weight Assessment Ratio Analysis (FF-SWARA) and the Fermatean Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (FF-RAFSI) approaches. The novel FF framework is employed to solve a critical problem encountered in the automobile manufacturing industry with the help of two related case studies. In addition, the criteria are identified and categorized regarding their influence degrees using a group decision approach based on an extended form of the Delphi with the aid of the Fermatean fuzzy sets. According to the conclusions of the analysis, the criteria "Accuracy" and "Quality" are the most effective measures. Also, the suggested hybrid model and its outcomes were tested by executing robustness and validation checks. The results of the analyses prove that the suggested integrated framework is a robust and practical decision-making tool.
Citation Count: 0
Assessing and selecting sustainable refrigerated road vehicles in food logistics using a novel multi-criteria group decision-making model
(Elsevier Science inc, 2024) Görçün, Ömer Faruk; Tirkolaee, Erfan Babaee; Kucukonder, Hande; Gargf, Chandra Prakash
In recent years, food loss and waste (FLW) have become an essential issue at the top of the international community's agenda. Since more people are afflicted by this problem every day, the global population would be forced into poverty and starvation without finding an immediate solution. Therefore, in order to decrease FLW, well-designed and sustainable food and cold supply chains (FCSCs) are needed. Additionally, refrigerated transportation systems can be crucial in developing sustainable supply chains. According to some empirical research, the technological capabilities of reefer vehicles or trailers differ significantly. Thus, selecting the reefer vehicle is a complex decision-making problem and selecting appropriate reefer vehicles may have a critical role in constructing successful supply chain systems and reducing food waste and loss. The current research proposes an efficient, robust and practical decision-making framework that can overcome uncertainties to tackle this decision-making problem. The managerial and strategic implications of the study also aid in decreasing FLW and restructuring FSC for industrial context and support to the UN's sustainable development goals (SDGs). Later, an exhaustive sensitivity analysis was conducted to examine the developed model's validity and application, confirming the model's robustness and dependability.
Citation Count: 14
Container vessel selection for maritime shipping companies by using an extended version of the Grey Relation Analysis (GRA) with the help of Type-2 neutrosophic fuzzy sets (T2NFN)
(Pergamon-Elsevier Science Ltd, 2022) Görçün, Ömer Faruk; Gorcun, Omer Faruk; Kundu, Pradip; Kucukonder, Hande
Contrary to expectations, based on occurring changes in customer behaviours related to consuming and shopping triggered by the pandemic, the global container shipping market has continued to grow during COVID 19. Experts estimate that these increases will continue in the future due to changing consumption habits. However, container shipping companies (CSCs) may soon encounter many troubles and challenging situations. They have an extremely fragile structure and may be entirely unprotected when they encounter unexpected situations sourced from external factors. (i.e., due to grounding of a ship, complete blockage of the Suez channel for three weeks can be given as a clear example of that). Hence, selecting an appropriate container vessel type can help construct a healthier container shipping system less influenced by adverse conditions for decision-makers and practitioners. Besides, it can provide a more effective and productive maritime transportation environment for all stakeholders. However, selecting a proper container vessel type is a complicated decision-making problem since many conflicting criteria and complex ambiguities exist. The current paper proposes an extended version of the GRA technique with the help of type-2 neutrosophic fuzzy sets (T2NFN) for capturing and processing uncertainties better than the traditional MCDM frameworks. According to the obtained results, C6, container carrying capacity, is the most influential criterion and the type of post-Suezmax container vessel is the best option for the CSCs, as it provides advantages at a satisfactory level for almost all criteria than others. After the proposed model was applied, a comprehensive sensitivity analysis (SA) was performed to test the validity of the T2NFN GRA approach. The results of SA approve the applicability, effectivity, and robustness of the model.
Electric Vehicle Selection for Industrial Users Using an Interval-Valued Intuitionistic Fuzzy Copras-Based Model
(Springer, 2024) Görçün, Ömer Faruk; Simic, Vladimir; Kundu, Pradip; Ozbek, Asir; Kucukonder, Hande
According to reports from international bodies such as the World Health Organization and the United Nations, transportation is one of the leading contributors to environmental pollution and climate change. Electric vehicles present a practical solution to reducing emissions, particularly for industrial users. However, industrial users' selection of electric vehicles involves different dynamics than individual users, making it a more complex process for companies. This paper aims to evaluate the selection criteria for electric vehicle fleets among industrial users using a novel multi-criteria decision-making framework based on interval-valued intuitionistic fuzzy sets. The model assesses various factors influencing industrial users' decisions and ranks the available electric vehicle options accordingly. The results indicate that driving range, purchase price, and charging time are the most influential factors in the decision-making process. Furthermore, the findings confirm that the Tesla Model S P100D is the most suitable option for industrial users, given its superior performance in these critical criteria.
Citation Count: 25
EVALUATING LOGISTICS VILLAGES IN TURKEY USING HYBRID IMPROVED FUZZY SWARA (IMF SWARA) AND FUZZY MABAC TECHNIQUES
(Vilnius Gediminas Tech Univ, 2021) Görçün, Ömer Faruk; Gorcun, Omer Faruk; Kucukonder, Hande
Positioning in the right location for organizing logistics activities is a determinative factor in the aspect of costs, effectivity, productivity, and performance of these operations carried out by logistics firms. The proper logistics village selection is a crucial, complicated, and time-consuming process for decision-makers who have to make the right and optimal decision on this issue. Decision-makers need a methodological frame with a practical algorithm that can be implemented quickly to solve these decision-making problems. Within this scope, the current paper aims to present an evaluation tool, which provides more reasonable and reliable results for decision-makers to solve the logistics village selection problem that is very complicated and has uncertain conditions based on fuzzy approaches. In this study, we propose the Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA), a modified and extended version of the traditional fuzzy Step-Wise Weight Assessment Ratio Analysis (F-SWARA) to identify the criteria weights. Also, we suggest applying the fuzzy Multi-Attributive Border Approximation area Comparison (F-MABAC) technique to determine the preference ratings of the alternatives. This combination has many valuable contributions. For example, it proposes to use a more reliable and consistent evaluation scale based on fuzzy sets. Hence, decision-makers can perform more reliable and reasonable pairwise comparisons by considering this evaluation scale. Besides, it presents a multi-attribute evaluation system based on the identified criteria weights. From this perspective, the proposed model is implemented to evaluate eight different logistics village alternatives with respect to nine selection criteria. According to the analysis results, while A8 is the most appropriate option, C1 Gross National Product (GNP) is the most significant criterion. A comprehensive sensitivity analysis was performed to test the robustness and validation of the proposed model, and the results of the analysis approve the validity and applicability of the proposed model. As a result, the suggested integrated MCDM framework can be applied as a valuable and practical decisionmaking tool to develop new strategies and improve the logistics operations by decision-makers.
Citation Count: 0
Evaluating the deep learning software tools for large-scale enterprises using a novel TODIFFA-MCDM framework
(Elsevier, 2024) Gligoric, Zoran; Görçün, Ömer Faruk; Gorcun, Omer Faruk; Gligoric, Milos; Pamucar, Dragan; Simic, Vladimir; Kucukonder, Hande
Deep learning (DL) is one of the most promising technological developments emerging in the fourth industrial revolution era for businesses to improve processes, increase efficiency, and reduce errors. Accordingly, hierarchical learning software selection is one of the most critical decision-making problems in integrating neural network applications into business models. However, selecting appropriate reinforcement learning software for integrating deep learning applications into enterprises' business models takes much work for decision-makers. There are several reasons for this: first, practitioners' limited knowledge and experience of DL makes it difficult for decision-makers to adapt this technology into their enterprises' business model and significantly increases complex uncertainties. Secondly, according to the authors' knowledge, no study in the literature addresses deep structured learning solutions with the help of MCDM approaches. Consequently, making inferences concerning criteria that should be considered in an evaluation process is impossible by considering the studies in the relevant literature. Considering these gaps, this study presents a novel decision-making approach developed by the authors. It involves the combination of two new decision-making approaches, MAXC (MAXimum of Criterion) and TODIFFA (the total differential of alternative), which were developed to solve current decision-making problems. When the most important advantages of this model are considered, it associates objective and subjective approaches and eliminates some critical limitations of these methodologies. Besides, it has an easily followable algorithm without the need for advanced mathematical knowledge for practitioners and provides highly stable and reliable results in solving complex decision-making problems. Another novelty of the study is that the criteria are determined with a long-term negotiation process that is part of comprehensive fieldwork with specialists. When the conclusions obtained using this model are briefly reviewed, the C2 "Data Availability and Quality" criterion is the most influential in selecting deep learning software. The C7 "Time Constraints" criterion follows the most influential factor. Remarkably, prior research has overlooked the correlation between the performance of Deep Learning (DL) platforms and the quality and accessibility of data. The findings of this study underscore the necessity for DL platform developers to devise solutions to enable DL platforms to operate effectively, notwithstanding the availability of clean, high-quality, and adequate data. Finally, the robustness check carried out to test the validity of the proposed model confirms the accuracy and robustness of the results obtained by implementing the suggested model.
Citation Count: 3
Evaluation of public transportation systems for sustainable cities using an integrated fuzzy multi-criteria group decision-making model
(Springer, 2023) Görçün, Ömer Faruk; Gorcun, Omer Faruk; Garg, Chandra Prakash; Kucukonder, Hande; Canakcioglu, Mustafa
In this era of increasing demand for mobility and rapid urban growth, there is a pressing need for a public transit system that is safe, fast, reliable, well-connected, and sustainable. Furthermore, it is essential to reduce the external costs associated with urban transportation, including environmental pollution, noise, congestion, and accidents, to foster sustainable cities. Choosing the right urban transportation system can meet this goal, but it is not an accessible business for decision-makers in the face of several conflicting criteria and ambiguities in the evaluation process. To cope with this, the current paper suggests a multi-criteria group decision-making (MCGDM) framework consisting of fuzzy BWM (Best-Worst method) and fuzzy MAIRCIA (Multi-Attribute Ideal-Real Comparative Analysis) techniques. This extended MCGDM approach has been applied to evaluate six urban transport systems, namely, Trams, Light Rail Trams, Metro (Subway), Bus Rapid Transport, Commuter Trains, and Public Buses based on 11 selection criteria which we have determined after consultation with highly experienced professionals. The fuzzy BWM technique is employed to identify the weights of the criteria. The fuzzy MAIRCA technique is utilized for ranking the alternatives using the calculated weights of the criteria. The proposed approach's validation has been examined with an extensive robustness check. The study is conducted from a general perspective, i.e., not restricted to a particular city. However, with the identified selection criteria, the proposed decision-making procedure can be repeated for a specific city considering any specific requirements, constraints, or limitations of that city.
Citation Count: 10
Evaluation of the route selection in international freight transportation by using the CODAS technique based on interval-valued Atanassov intuitionistic sets
(Springer, 2023) Görçün, Ömer Faruk; Gorcun, Omer Faruk; Kucukonder, Hande
The selection of a proper international freight transport route is one of the crucial tasks for decision-makers since it can affect costs, efficiency, and transportation performance. Besides, the selection of suitable and appropriate freight routes can also reduce external costs of transportation such as emissions, noise, traffic congestions, accidents, and so on. Route selection in international transportation is a complicated decision-making problem as many conflicting factors and criteria affect the assessment process. It has been observed that there is no mathematical model and methodological frame used for solving these selection problems, and decision-makers make decisions on this issue based on their own experiences and verbal judgments in the research process. Therefore, a methodological frame is required to make rational, realistic, and optimal decisions on route selection. From this perspective, the current paper proposes using the IVAIF CODAS, an extended version of the traditional CODAS techniques, and using the Atanassov interval-valued intuitionistic fuzzy sets (IVAIFS) for processing better the existing uncertainties. The proposed model is applied to solve the route selection, a real-life decision-making problem encountered in international transportation between EU countries and Turkey. According to the results of the analysis, option A6 (i.e., Route-6 (Bursa-Istanbul-Pendik-Trieste (Ro-Ro)-Austria-Frankfurt/Germany) has been determined as the best alternative. These obtained results have been approved by a comprehensive sensitivity analysis performed by using different MCDM techniques based on interval-valued intuitionistic fuzzy sets. Hence, it can be accepted that the proposed model is an applicable, robust, and powerful mathematical tool; also, it can provide very reliable, accurate, and reasonable results. As a result, the proposed model can provide a more flexible and effective decision-making environment as well as it can provide valuable advantages to the logistics and transport companies for carrying out practical, productive, and lower cost logistics operations.
Citation Count: 0
Evaluation of the second-hand LNG tanker vessels using fuzzy MCGDM approach based on the Interval type-2 fuzzy ARAS (IT2F-ARAS) technique
(Pergamon-elsevier Science Ltd, 2024) Görçün, Ömer Faruk; Kundu, Pradip; Kucukonder, Hande; Senthil, S.
Selecting appropriate LNG tankers is paramount in the maritime sector. Opting for suitable second-hand LNG vessels is a significant and efficient strategy for managing transportation operations effectively and meeting industry standards. Given LNG tanker specifications and shipbuilding capacity, the second-hand LNG tanker market adequately meets maritime industry demands. Thus, there is a strong motivation to evaluate the current second-hand vessel market. However, uncertainties prevail, necessitating decision-makers to employ a resilient and practical methodological framework to address uncertainties and complex decision-making scenarios effectively. This study proposes a decision-making framework integrating the Delphi and Additive Ratio Assessment (ARAS) methods, leveraging interval type-2 fuzzy sets (IT2FSs). This framework resolves real-life challenges associated with selecting second-hand LNG tankers, demonstrating the practicality of the approach. Using IT2FSs, the Delphi method identifies critical criteria influencing second-hand tanker vessel selection. "Cargo carriage capacity" emerged as the most influential criterion, followed by "purchasing costs" and "year of construction." Moreover, "Mediterranean Energy" was deemed the most suitable second-hand LNG tanker among the six alternatives assessed. Thorough sensitivity analysis validated the proposed model and its implications, confirming its validity and applicability.
Citation Count: 9
Evaluation of the Special Warehouse Handling Equipment (Turret Trucks) Using Integrated FUCOM and WASPAS Techniques Based on Intuitionistic Fuzzy Dombi Aggregation Operators
(Springer Heidelberg, 2023) Görçün, Ömer Faruk; Gorcun, Omer Faruk; Kucukonder, Hande
Turret trucks used for special warehousing operations have exceptional abilities, qualifications, and working principles than other warehousing handling equipment. Also, at the same time, if decision-makers cannot select as proper to needs, the cost of being idle of these kinds of machines is very high. According to the comprehensive literature review and the paper's findings, evaluating turret trucks is complex, complicated, and time-consuming for decision-makers, as many conflicting criteria and uncertainties affect the evaluation processes. Hence, it is required to employ a practical, powerful, and practical multi-criteria decision-making (MCDM) approach that can handle ambiguities to solve these kinds of problems. For this purpose, the current paper proposes an extended version of a hybrid decision-making tool consisting of FUCOM (Full Consistency Method) and the WASPAS (Weighted Aggregated Sum Product Assessment) technique with the help of the intuitionistic fuzzy Dombi aggregation operators. It can help to select the appropriate turret trucks that can help reduce the costs of remaining idle and provide economic effectivity of logistics and warehousing operations. According to the outcomes of the suggested model, the width, lift motor power and lift height of the turret trucks are the most critical and influential criteria, as they determine the corridor width, accordingly space utilization, warehousing capacity, and unit warehousing costs. Finally, the intuitionistic fuzzy model is applied to solve the turret truck selection problems. A comprehensive sensitivity analysis consisting of three phases was performed to test the validation of the proposed model and its obtained results. The sensitivity analysis results approve the proposed model's applicability and validity. Thus, the analysis results validated that the proposed approach is a robust and practical MCDM framework, and its results are accurate and reasonable.
Citation Count: 21
An integrated fuzzy MCDM approach based on Bonferroni functions for selection and evaluation of industrial robots for the automobile manufacturing industry
(Pergamon-Elsevier Science Ltd, 2023) Garg, Chandra Prakash; Gorcun, Omer F.; Kundu, Pradip; Kucukonder, Hande
In recent years, there have been dramatic changes in manufacturing systems in many industries depending on technological developments. Robotics is one of the essential components of these changes. Today, the usage of robotics in manufacturing processes has become widespread in almost all industries. Also, it has become a very strong desire ever-increasing for even small and medium-sized enterprises at present. Almost all the previous studies emphasized that industrial robot selection is a highly complex decision-making problem as there are many conflicting factors and criteria. Besides, different and advanced specifications of these robotics added by robotic manufacturers have caused to increase the complexities much more. Hence, decision-makers encounter more complicated decision-making problems affected by many uncertainties. Because of that, an integrated fuzzy group MCDM framework can help overcome many ambiguities proposed in the current paper. The proposed fuzzy integrated model consists of the fuzzy SWARA (F-SWARA'B) and the fuzzy CoCoSo (F-CoCoSo'B), which are extended with the help of the Bonferroni function. The model selected the appropriate industrial robotics used in the automotive industry by considering 15 criteria and ten alternatives. According to the result of the study, the three most significant criteria have been determined: Working Accuracy, Reaching Distance, and Performance; and the most suitable option is the A8. The obtained results were validated with the help of a comprehensive sensitivity analysis consisting of different 150 scenarios. The results are also compared with some existing techniques. The sensitivity analysis results approve the validity and applicability of the proposed model.
Citation Count: 1
An integrated model for road freight transport firm selection in third-party logistics using T-spherical Fuzzy sets
(Pergamon-elsevier Science Ltd, 2024) Gorcuen, Omer Faruk; Chatterjee, Prasenjit.; Stevic, Zeljko.; Kucukonder, Hande
The efficient selection of road freight transport (RFT) firms plays a critical role in constructing well-operating logistics systems for large-scale third-party logistics (3PL) providers. However, the decision-making process for such selection is often complex and uncertain due to various influential criteria and dynamic industry nature. To address this challenge, a novel decision-making model that integrates Delphi, CRiteria Importance Through Intercriteria Correlation (CRITIC) and Combined compromise ranking solution (CoCoSo) methods based on T-Spherical Fuzzy sets has been proposed in this paper. The model integrates expert opinions with an extensive literature review to identify the influential criteria and their corresponding weights. Subsequently, it employs a comprehensive evaluation approach to rank the RFT firms based on their performance. The model accommodates uncertainties and subjectivity by utilizing T-Spherical Fuzzy Numbers, offering robustness and transparency in decision-making. A case study involving 15 evaluation criteria and 12 RFT firms were selected to demonstrate the applicability and aptness of the proposed model. Flexibility and Integrability to different transport modes emerged as the two most essential criteria, whereas RFT firm A2 emerged as the best alternative with the highest performance score of 3.0861, followed by RFT firm A7 with a score value of 3.0499.
Citation Count: 10
Medical device selection in private hospitals by integrated fuzzy MCGDM methods: A case study in choosing MRI (Magnetic Resonance Imaging) system
(Taylor & Francis Ltd, 2022) Görçün, Ömer Faruk; Gorcun, Omer Faruk; Kucukonder, Hande
This paper investigates medical device selection problem in healthcare organizations. As compared to numerous research works on supplier/equipment selection problems in diverse areas of applications, surprisingly, the number of works is less in case of the healthcare industry. In this paper, as a case study, we consider MRI (Magnetic Resonance Imaging) system selection problem in private hospitals. Because of non-radiation and advanced technology, MRI has emerged as the imaging modality of choice in diagnostic and monitoring treatment. In this study, we identify 16 brands (alternatives) of MRI systems and select 10 selection criteria that are chosen with the consultation of a group of experts in the field of hospital management. Methodological framework as suggested to deal with the device selection problem includes an integrated MCGDM (multi-criteria group decision-making) approach which is a combination of fuzzy PSI (preference selection index) method and fuzzy MARCOS (measurement of alternatives and ranking according to compromise solution) method. To cope with the vagueness in linguistic evaluation done by the decision makers, fuzzy numbers have been used in the representation of linguistic terms. The integrated fuzzy MCGDM method is applied to evaluate and rank the alternatives, and the results are analyzed through a comprehensive sensitivity analysis. Total 100 scenarios are created by changing the weight of each criterion as computed using fuzzy PSI technique to examine the effects of change of the weights of the criteria on the ranking results. It is observed that out of 100 scenarios, alternative 8 (A8) remains the best option for 96 scenarios, and it is the second-best option only for the remaining 4 scenarios. Also, the results of the hybrid fuzzy MCGDM technique have been compared with the results obtained by using other MCGDM methods.
Citation Count: 1
A novel model based on the fuzzy Grey Relational Analysis (F-GRA) approach for selecting the appropriate high-speed train set
(Springer, 2023) Garg, Chandra Prakash; Gorcun, Omer F.; Kucukonder, Hande
The high-speed train (HST) system is one of the most critical components of national and international passenger transportation networks. Selecting the appropriate train sets is a critical task for railway operators to build an efficient, productive, safe, inexpensive and environmentally friendly passenger transport network system. On the other hand, selecting the proper HST set is a highly complex process since many conflicting criteria, and decision alternatives make it difficult for decision-makers. This paper suggests the fuzzy Grey Relational Analysis technique. In addition, the fuzzy technique proposed in the current paper has been implemented in two ways: using both the experts' linguistic evaluations and crisp numbers to compare real numerical values and fuzzy evaluations. A comprehensive sensitivity analysis was then conducted to assess the validation of the proposed fuzzy technique and its results in applying this method. The decision alternative of A8 Siemens is the best option for all scenarios, and it has been observed that there are slight differences, which cannot change the overall result in the ranking positions of the options. The analysis results prove that the fuzzy method can be applied to solve these complicated decision-making problems and that the obtained results are robust, accurate, applicable, and realistic.
Citation Count: 0
A novel performance evaluation technique based on integrated weighting approach: A case study in the field of sport management
(Growing Science, 2021) Görçün, Ömer Faruk; Kucukonder, Hande
It is a fact accepted by everybody that football is the most popular sport around the world. The result of a derby match may be very important for millions of people. Even the time seems to stop on a match day for so many people. Show and entertainment are the most important aspects of football. If soccer players have a high performance, a match may provide pleasure and excitement to audiences. Briefly, the performance and quality of soccer players are the key factors, which draw audiences. Goalkeepers are also one of the important components of football like other players playing different positions such as strikers, mid-fielders, and defenders. Moreover, a goalkeeper can affect the result of a match positively or negatively. Therefore, with the help of a mathematical approach as the methodological framework, it can be seen that the examination of the performance of goalkeepers can be beneficial for decision-makers performing in the fields of sport and the future studies. The current paper proposes an improved integrated multi-criteria decision-making approach to evaluate the selection of goalkeepers; and this model can be applied for goalkeeper's performance analysis. The proposed model combines the weights of criteria calculated with the help of both the CRITIC and the PSI techniques by applying the weight aggregation operator. It also ranks the decision alternatives by implementing the WASPAS technique based on the final criteria weights obtained by using the weight aggregation operator. In addition, a comprehensive sensitivity analysis consisting of three stages was performed to verify the validation of the suggested hybrid model. It has been observed that All has remained the best option for all scenarios. As a result, the results of the sensitivity analysis prove that the proposed hybrid MCDM technique is a very useful, strong and applicable approach. Also, the results obtained by applying the proposed model are accurate, realistic, and reasonable according to the results of the validation test. (C) 2021 by the authors; licensee Growing Science, Canada.
Citation Count: 13
The selection of appropriate Ro-Ro Vessel in the second-hand market using the WASPAS' Bonferroni approach in type 2 neutrosophic fuzzy environment
(Pergamon-Elsevier Science Ltd, 2023) Görçün, Ömer Faruk; Pamucar, Dragan; Krishankumar, Raghunathan; Kucukonder, Hande
The second-hand vessel market has quite different dynamics than the market of the new-building vessel, and highly complicated and conflicting criteria and many uncertainties affect the ship selection process. Therefore, it is required to use a robust mathematical model to solve these kinds of decision-making problems. For this purpose, this paper presents an extended version of WASPAS (Weighted Aggregated Sum Product ASsessment) techniques with the help of T2NN based on the Bonferroni function (T2NN WASPAS'B). The three main focal points of the proposed approach are (i) setting the influential criteria to select the appropriate Ro-Ro vessel in the second-hand vessel market; and (ii) presenting a flexible group decision-making approach, which is proper to real decision-making problems. (iii) detecting the interrelations among criteria and eliminating the negative impacts of undesirable and excessive values in input variables on the results. Practical use of the proposed approach is demonstrated to select the appropriate Ro-Ro vessel in the second-hand market. The analysis results show that the most effective and determinative factor is Trailer Lane length, and the most effective alternative is GREIFSWALD. Besides, the consistency and validity of the obtained results have been verified with the help of a stability and robustness check. The results prove that the proposed novel T2NN WASPAS'B model is robust, powerful, and reliable for making rational and realistic decisions.
Citation Count: 2
Selection of the best Big Data platform using COBRAC-ARTASI methodology with adaptive standardized intervals
(Pergamon-elsevier Science Ltd, 2024) Görçün, Ömer Faruk; Simic, Vladimir; Gorcun, Omer Faruk; Kucukonder, Hande
The advanced technologies emerging in Industry 4.0 are forcing companies in different industries to review their business models and become more compatible with advanced technological practices. While traditional business models are increasingly inadequate in the face of increasing competition, business models developed thanks to advanced technologies such as deep learning and machine learning have begun to replace them. However, developing business intelligence and intelligent applications using these technologies requires more data processing. In this context, Big Data technology is a unique instrument in providing the data businesses need to design more intelligent systems. In conclusion, the Big Data platform can significantly speed up the processes of structuring and processing the data and information generated and increase businesses' efficiency, performance, and agility. However, being a relatively new concept, the knowledge about the Big Data concept is limited, leading to several challenges for decision-makers concerning choosing the appropriate platform. Also, the number of studies on this subject is highly scarce. Hence, practitioners in various industries lack sufficient support from the research society on this issue. We could not find crisp and definite values to evaluate the BD alternatives despite comprehensive investigation. In that regard, as data, we addressed appraisals and opinions of IT professionals with vast knowledge and experience in assessment, selection, installation, and operation. We developed a novel decision-making model to evaluate and select the most proper BD platforms by processing these data. In this connection, the current investigation suggests a novel, robust, practical decision-making model for defining the combination of the weight of criteria based on pairwise comparisons of adjacently ranked criteria (COmparisons Between RAnked Criteria- COBRAC) and the ARTASI (Alternative ranking technique based on adaptive standardized intervals -ARTASI). It can handle complex ambiguities encountered in appraisal processes to address the Big Data platform selection problem. In addition, the current work developed a negotiation process quantitificated to determine the influential criteria affecting the selection of the Big Data platform. When we evaluate the outcomes of the suggested model, the most influential criterion affecting the selection of the Big Data platform is C12 "Ease of Use." in addition, the most suitable Big Data platform for large-scale enterprises has been identified as A3 Microsoft SQL Server. The proposed model and its results have been validated based on extensive sensitivity and comparison analysis. These results also offer practical and managerial implications for the industry. Although many studies indicate that installation cost and speed are the most critical factors, this research found that, unlike these studies, ease of use is the most critical factor in choosing a BD platform. In this context, the BD alternative that provides the highest ease of use can produce more efficient results and reduce complexities in collecting and processing high volumes of structured and unstructured data.
Citation Count: 5
Selection of tramcars for sustainable urban transportation by using the modified WASPAS approach based on Heronian operators
(Elsevier, 2024) Görçün, Ömer Faruk; Pamucar, Dragan; Kucukonder, Hande
The wrong design of rail system vehicle fleets is one of the most critical problems in terms of urban transportation. Light rail system fleets in many large cities, including Istanbul, consist of various types and feature vehicles. It creates significant problems in integrating each rail system vehicle into the system. In addition, while it is necessary to keep an inventory of spare parts for each different type of vehicle, it requires different qualifications for professionals involved in processes such as maintenance and repair, leading to extra costs. In this context, the study's primary purpose is to determine the most suitable light rail vehicles for urban transportation systems and create vehicle fleets accordingly. In that regard, the study aims to provide a reliable and practical decision-making model that can be used as a roadmap for decision-makers when choosing tramcars to solve these problems. The present work proposes a hybrid procedure integrating the Best and Worst Method (BWM) and Power-Heronian Weighted Aggregated Sum Product Assessment (WASPAS'PH) approaches. The most critical implication of the work indicated that the acquisition cost per tramcar set (0.148) is still the most influential factor. The economic lifespan of tramcars (0.037), the number of seats in a vehicle set (0.041), and energy consumption (0.072) have followed the most significant criterion, respectively. Besides, it highlighted that the A14 Brand CR (0.7819) is the most appropriate option for well-structuring the urban light rail system fleet. An extensive validation test to check the suggested model's robustness confirmed the procedure's stability and consistency.
Citation Count: 16
Sustainability performance analysis of micro-mobility solutions in urban transportation with a novel IVFNN-Delphi-LOPCOW-CoCoSo framework
(Pergamon-Elsevier Science Ltd, 2023) Görçün, Ömer Faruk; Kucukonder, Hande; Kaya, Sema Kayapinar; Gorcun, Omer Faruk
Almost all megacities worldwide are under pressure from environmental pollution and excessive resource usage due to rapid urbanization and increasing urban population. Within this scope, micro-mobility solutions (MMSs), an extension to the primary urban transportation network, have become even more critical recently. However, when we executed a preliminary investigation concerning MMSs' sustainability, we noted some critical theoretical and managerial gaps: (1) the number of studies assessing MMSs using decision-making approaches is excessively scarce, (2) no paper in the literature deals with the MMSs' sustainability performance, and (3) there are no commonly accepted criteria set to assess the sustainability of the MMSs in the literature. The current study aims to present a practical and robust decision-making framework that can over-come excessively complicated uncertainties to evaluate the sustainability performance of MMSs. Further, it suggests a novel methodological framework, i.e., Delphi, Loga-rithmic Percentage Change-Driven Objective Weighting (LOPCOW), and Combined Compromise Solution (CoCoSo) methods with interval-valued fuzzy neutrosophic number (IVFNN) informa-tion, which can be defined as a reconciliation tool to set the criteria affecting the assessment processes. Findings present that computing time, scenic adoption, and accidents are the foremost criteria, whereas mini-electric VH, powered standing scooter, and powered seated scooter are the most promising MMSs, respectively. Findings reveal that computing time, scenic adoption, and accidents are the critical factors for the sustainability assessment of MMSs, whereas mini-electric VH, powered standing scooter, and powered seated scooter are the most promising MMSs, respectively. The current paper's overall outcomes and findings can assist practitioners and policy-makers in the urban transportation industry in setting sustainability policies and investing in the more rational and sustainable MMSs.