Browsing by Author "Gorcun, Omer Faruk"

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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: 10
Analysis of efficiency and performance of global retail supply chains using integrated fuzzy SWARA and fuzzy EATWOS methods
(Springer, 2022) Görçün, Ömer Faruk; Zolfani, Sarfaraz Hashemkhani; Canakcioglu, Mustafa
The current paper aims to fill the two severe and significant gaps in the literature related to global retail chains. First, it presents the criteria set identified by performing comprehensive fieldwork together with experts highly experienced and have extensive knowledge of the retailing industry and a detailed literature review. Secondly, it proposes a robust, applicable, and powerful novel integrated MCDM framework dealing with many complicated uncertainties. As one of the significant practical and managerial implications, the current paper highlights the significance of sustainable retailing operations to better global retail chains. After the proposed model was implemented, a comprehensive sensitivity analysis was performed to test the validation of the model and its obtained results. According to the validation test results, A12 Walmart&ASDA has remained the best option for all scenarios. It has been observed that there are slight changes that did not change the overall results in the ranking performance of some decision alternatives. As a result, the analysis results prove that the proposed integrated fuzzy approach can be applied to solve highly complex decision-making problems encountered in various fields and the retailing industry.
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: 18
The blockchain technology selection in the logistics industry using a novel MCDM framework based on Fermatean fuzzy sets and Dombi aggregation
(Elsevier Science Inc, 2023) Görçün, Ömer Faruk; Pamucar, Dragan; Biswas, Sanjib
Logistics is a sophisticated system involving third-party logistics (3PL) providers, freight forwarders, warehousing companies, and transport service producers in various transport modes, such as road, rail, air, maritime, and multimodal transportation. Furthermore, it is possible to add customs clearance agencies, insurance companies, banks, and relevant institutions and organizations to the system. Effective logistics systems must sustainably provide customers with quality and satisfactory logistics services using data shared over advanced technologies. Nevertheless, data and information on logistics are usually challenging to collect, process, and understand, as they are primarily unstructured, unreachable, and unstandardized. Blockchain is a new and advanced technology promising to eliminate or mitigate the adverse effects of these difficulties. However, blockchain technology practices in the logistics industry are extraordinarily scarce; and a few blockchain platforms have attempted to produce solutions for a few large-scale and global logistics firms. Hence, the digital transformation process involving blockchain technology for a logistics company encounters the challenge of selecting an appropriate blockchain platform for the logistics industry's needs. Although studies have been carried out in the relevant literature to select a suitable blockchain platform for various industries, few of these studies dealt with selecting the best blockchain platform for the logistics industry. Hence, experimental studies on choosing the proper blockchain platform in the logistics industry that tries to manage outstandingly complicated relations and linkages among stakeholders are currently inadequate. The current study presents a novel, robust, practical, and powerful decision-making tool that can also overcome highly complex uncertainties to identify the most feasible blockchain technology for the logistics industry. The robustness of the study's findings is validated with comprehensive sensitivity and comparative analyses.
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.
Citation Count: 1
Determining the factors affecting transportation demand management and selecting the best strategy: A case study
(Elsevier Sci Ltd, 2024) Görçün, Ömer Faruk; Korucuk, Selcuk; Gorcun, Omer Faruk
Demand management in transportation services, as well as demand sustainability, demand planning, and demand implementation are critical components in service quality and environmental sustainability. It is evident that developing a transportation system, particularly one responsive to society's aspirations and demands, will result in long-term and sustainable success for enterprises. Transportation demand management and strategies can produce alternative perspectives at a desirable and sufficient level to handle problems in the field while considering the obstacles. Considering the elements influencing transportation demand management in logistics enterprises, this study aims to evaluate factors affecting transportation demand management and select the best strategy. The study was carried out on logistic firms with a corporate identity in the Turkish province of Samsun (Turkiye), engaged in international transportation activities to define the criteria affecting transportation demand management and select the best transportation demand strategy. The constituents from the literature review were analyzed using the q-rung orthopair fuzzy MCDA methodology. "Freight Transportation" was determined to be the most crucial measure affecting transportation demand management, while "Competition Legislation and Regulations Regulation" was the least important factor. The rapid expansion in the number of companies participating in freight transport and their capacity was evaluated as the essential aspect for the relevant logistics companies in transport demand management. The "Strategy for Prioritizing High Occupancy Vehicles" is the best transportation strategy based on the weights of the transportation demand management factors. Because of the implementation of this strategy in logistics organizations, this study is regarded as a significant indicator of competitiveness to ensure efficiency and effectiveness. The defined transport demand strategy also represents an exemplary model of the measures that need to be developed to increase the demand preference for sustainable transport.
Citation Count: 8
Efficiency analysis technique with input and output satisficing approach based on Type-2 Neutrosophic Fuzzy Sets: A case study of container shipping companies
(Pergamon-Elsevier Science Ltd, 2023) Görçün, Ömer Faruk; Gorcun, Omer Faruk; Canakcioglu, Mustafa; Tirkolaee, Erfan Babaee
This work tries to discuss and evaluate the advantages and superiorities of the extended Efficiency Analysis Technique with Input and Output Satisficing (EATWIOS) method based on Type-2 Neutrosophic Fuzzy Numbers (T2NFNs). The suggested model is maximally stable and robust by considering sensitivity analysis results which demonstrates a new performance analysis approach based on T2NFN sets. The proposed model deals with the input and output criteria and considers existing uncertainties arising from insufficient information and the dy-namic structure of the industries. The model's basic algorithm has a unique structure compared to the previous performance analysis technique, and it does not require applying additional weighting techniques to identify the criteria weights. To the best of our knowledge, the extended version of the EATWIOS technique based on the T2NFN set is presented for the first time. The developed model provides reasonable and logical results to practitioners because it deals with satisfactory outputs instead of optimal outputs. This model is an immensely strengthened version of the EATWIOS technique, as the T2NFN sets treat predictable and unpredictable un-certainties. The suggested T2NFN-EATWIOS is then applied to a real-world assessment problem in the container shipping industry. The obtained results are pretty reasonable and logical. Moreover, the results of a compre-hensive sensitivity analysis with three stages approve the robustness of the suggested 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: 13
Evaluating and selecting sustainable logistics service providers for medical waste disposal treatment in the healthcare industry
(Elsevier Sci Ltd, 2023) Görçün, Ömer Faruk; Aytekin, Ahmet; Korucuk, Selcuk; Tirkolaee, Erfan Babaee
Health institutes are structurally growing depending on the population increase and escalating demands for health services. As a negative result, the health industry produces more healthcare waste daily. Its efforts and resources cannot be sufficient to dispose of such medical wastes as the quantity and variety continue to increase. Therefore, developing solution partnership relations with logistics service providers specialized in collecting, storing, and disposing healthcare waste may be a beneficial and fruitful step for solving this problem. However, the evaluation and selection of service suppliers for healthcare waste disposal may not always result in success. Hence, the present work develops a robust integrated methodology on the basis of Step-wise Weight Assessment Ratio Analysis (SWARA) and COmplex PRoportional ASsessment (COPRAS) techniques based on Interval-Valued Fermatean Fuzzy Sets (IVFFSs) for healthcare decision-makers to make more rational and optimal decisions concerning service supplier selection. The proposed model based on the IVFFSs can also overcome incredibly complicated uncertainties in the assessment processes. A large-scale international hospital chain in Turkey is investigated using the developed methodology to find reasonable and logical solutions to assess and select the best Medical Waste Disposal and Logistics (MWDL) firm. It is revealed that the most important criterion is Storage Conditions where Republic Services, Inc is the most successful supplier of MWDL. Finally, theoretical and practical implications are discussed in detail in order to provide useful managerial insights and decision aids to assist in improving the sustainability of healthcare industry.
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: 2
Evaluation of container port sustainability using WASPAS technique using on type-2 neutrosophic fuzzy numbers
(Pergamon-Elsevier Science Ltd, 2023) Görçün, Ömer Faruk; Kundu, Pradip; Gorcun, Omer Faruk
According to the common opinion in the literature, the sustainability of container ports is a tremendously complex topic owing to the maritime sector's excessively dynamic form and many highly complex, predictable and unpredictable uncertainties in this industry. The current paper proposes two powerful, practical, inspiring approaches to fill these gaps. It proposes a novel type-2 neutrosophic fuzzy numbers (T2NFNs) based Delphi method to determine the criteria logically and optimal and extends the WASPAS technique based on the T2NFNs for evaluating the alternatives. The current paper presents practical managerial implications that many stakeholders can consider, such as port authorities, ship owners, logistics service providers, governments, and local authorities, when making strategic and managerial decisions. In addition, the results of a comprehensive sensitivity analysis performed to test the robustness and applicability of the model approve the validity of the proposed T2NFN-based integrated approach.
Citation Count: 0
Evaluation of Industry 4.0 strategies for digital transformation in the automotive manufacturing industry using an integrated fuzzy decision-making model
(Elsevier Sci Ltd, 2024) Görçün, Ömer Faruk; Mishra, Arunodaya Raj; Aytekin, Ahmet; Simic, Vladimir; Korucuk, Selcuk
The current paper proposes a methodological frame to identify the best Industry 4.0 (I4) strategy for the automotive manufacturing industry as a roadmap for companies to make a more straightforward digital transformation. We noticed a critical research gap when we performed an extensive literature review. Although there are many studies available that assess the readiness of companies for I4, only a few deal with decision -making in terms of sustainable development, and none have applied that to the automotive industry. Practitioners can apply the proposed model to determine the strategy based on technological developments in I4. The current paper proposes an extended version of the combined compromise solution approach with the help of the picture fuzzy sets. According to the paper 's results, by using the proposed model, developing a new business model based on technological improvements is the best strategy for the digital transformation of the automotive industry. Also, the lack of research and development implementations on I4 implementation is the most influential factor. Hence, practitioners in the automotive industry know the significance of research and development in reaching successful results for digital transformation. The acquired outcomes of the paper show that developing technology -based new business models is the best strategy for the automotive manufacturing industry concerning digital transformation instead of accommodating traditional business models and high technology utilization.
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: 0
Evaluation of shared micro-mobility systems for sustainable cities by using a consensus-based Fermatean fuzzy multiple objective optimization and full multiplicative form
(Pergamon-elsevier Science Ltd, 2024) Saha, Abhijit; Görçün, Ömer Faruk; Gorcun, Omer Faruk; Pamucar, Dragan; Arya, Leena; Simic, Vladimir
In Turkey, the transportation industry's greenhouse gas (GHG) emissions increased by 147.1% between 1990 and 2019. Today, this transportation industry (i.e., freight and passenger) is among the significant contributors to greenhouse gas emissions in Turkey's megacities. Moreover, 65.43% of short-distance trips between home to work and home to school have been made by private automobiles in Istanbul and increasing concerns about environmental pollution have led practitioners to seek practical, robust, and effective solutions to reduce GHG emissions. Shared electric scooters have rapidly become popular for end-users and practitioners in megacities, depending on their valuable advantages. However, the rapid spread of micro-mobility, characterized by escooters, has also raised questions about this system's sustainability, suitability, and applicability. Thus, there are some critical and noteworthy gaps in this issue. This study investigates the factors affecting the suitable e-scooter selection for a sustainable urban transport system. Besides, it aims to develop a methodological framework for assessing the available e-scooter alternatives. For this purpose, a novel negotiation approach, a new form of the Delphi technique, was developed with the help of Fermatean fuzzy sets to identify the influential criteria. Also, the current paper presents a consensus-based MULTIMOORA (Multiple Objective Optimization on the basis of Ratio Analysis plus Full Multiplicative Form) decision-making model based on Fermatean fuzzy sets to address the appraisal problem concerning e-scooter selection. The current paper indicated that economic measures such as acquisition price and upkeep costs affect the e-scooter selection processes. In addition, an optimization model based on cross-entropy and dispersion measures is utilized to compute criteria weights. It highlighted that the costs of e-scooters are still high, and operators consider these criteria instead of the technical and operational features of the e-scooters. Finally, the validity check executed to test the robustness and trustworthiness of the model affirms the model's firmness and trustworthiness.
Citation Count: 24
Evaluation of the European container ports using a new hybrid fuzzy LBWA-CoCoSo'B techniques
(Pergamon-Elsevier Science Ltd, 2022) Görçün, Ömer Faruk; Gorcun, Omer Faruk
Reducing transportation costs is one of today's global supply chains' essential tasks. For this purpose, as the crucial players of the worldwide supply chains, the international container shipping companies try to find optimal ways to reduce the shipping costs. Unnecessary transhipment and displacement operations are the leading causes of high logistics and transport costs. Selecting the most appropriate container seaport is one of the most effective ways to minimize these costs. The proper container port choice can provide an optimum container shipping system consisting of productive, efficient, and less costly container lines. Besides, a methodological framework is needed to address these kinds of highly complex decision-making issues. To serve this purpose, this paper proposes a fuzzy integrated MCDM approach consisting of the Fuzzy LBWA and fuzzy CoCoSo'B techniques. The consistency and stability of the model applied to evaluate the European container ports have been approved by a comprehensive sensitivity analysis. When the obtained results are evaluated, While C5 Port Costs has been determined as the most influential criterion, A2 Port of Antwerp (2.034) is the best and A10 Port of Barcelona (1.266) is the worst alternative. The obtained results were validated by comparing the results of the implemented popular MCDM frameworks with the help of Spearman Correlation Coefficient (SCC) [(SCC (MABAC) = 1.00; SCC (MAIRCA) = 1.00 and SCC (CoCoSo) = 0.915]. All SCC values have over 0.80 that can be accepted high correlation coefficient. The analysis results prove that the proposed fuzzy technique can be implemented to solve the highly complex decision-making problems faced in the maritime industry.
Citation Count: 16
Evaluation of the pharmaceutical distribution and warehousing companies through an integrated Fermatean fuzzy entropy-WASPAS approach
(Emerald Group Publishing Ltd, 2022) Görçün, Ömer Faruk; Gorcun, Omer Faruk; Ecer, Fatih; Pamucar, Dragan; Karama, Caglar
Purpose Pharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to successfully store and distribute their medicines. Hospitals, health institutes, and pharmacies must maintain extra stock to respond requirements of the patients. Nevertheless, there is an inverse correlation between the level of medicine stock and logistics service level. The high stock level held by health institutions indicates that we have not sufficiently excellent logistics systems presently. As such, selecting appropriate logistics service providers (drug distributors) is crucial and strategic for PSCs. However, this is difficult for decision-makers, as highly complex situations and conflicting criteria influence such evaluation processes. So, a robust, applicable, and strong methodological frame is required to solve these decision-making problems. Design/methodology/approach To achieve this challenging issue, the authors develop and apply an integrated entropy-WASPAS methodology with Fermatean fuzzy sets for the first time in the literature. The evaluation process takes place in two stages, as in traditional multi-criteria problems. In the first stage, the importance levels of the criteria are determined by the FF-entropy method. Afterwards, the FF-WASPAS approach ranks the alternatives. Findings The feasibility of the proposed model is also supported by a case study where six companies are evaluated comprehensively regarding ten criteria. Herewith, total warehouse capacity, number of refrigerated vehicles, and personnel are the top three criteria that significantly influence the evaluation of pharmaceutical distribution and warehousing companies. Further, a comprehensive sensitivity analysis proves the robustness and effectiveness of the proposed approach. Practical implications The proposed multi-attribute decision model quantitatively aids managers in selecting logistics service providers considering imprecisions in the multi-criteria decision-making process. Originality/value A new model has been developed to present a sound mathematical model for selecting logistics service providers consisting of Fermatean fuzzy entropy and WASPAS methods. The paper's main contribution is presenting a comprehensive and more robust model for the ex ante evaluation and ranking of providers.
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.