Browsing by Author "Pamucar, Dragan"

Now showing 1 - 12 of 12

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: 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: 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: 4
Foreign market selection of suppliers through a novel REF-Sort technique
(Emerald Group Publishing Ltd, 2022) Görçün, Ömer Faruk; Gorcun, Omer Faruk; Ecer, Fatih; Pamucar, Dragan; Karamasa, Caglar
Purpose The present study aims to provide a practical and robust assessment technique for assessing countries' investability in global supply chains to practitioners. Thus, the proposed approach can help decision-makers evaluate and select appropriate countries in the expansion process of the global supply chains and reduce risks concerning country (market) selection. Design/methodology/approach The present study proposes a novel decision-making approach, namely the REF-Sort technique. The proposed approach has many valuable contributions to the literature. First, it has an efficient basic algorithm and can be applied to solve highly complicated decision-making problems without requiring advanced mathematical knowledge. Besides, some characteristics differentiate REF-Sort apart from other techniques. REF-Sort employs the value or value range that reflects the most typical characteristic of the relevant class in assignment processes. The reference values in REF-Sort and center profiles are similar in this regard. On the other hand, class references can be defined as ranges in REF-Sort. Secondary values, called successors, can also be employed to assign a value to the appropriate class. REF-Sort can also determine the reference and successor values/ranges independently of the decision matrix. In addition, the proposed model is a maximally stable and consistent decision-making tool, as it is resistant to the rank reversal problem. Findings The current papers' findings indicate that countries have different features concerning investment. Hence, the current paper pointed out that only 22% of the 95 countries are investable, whereas 19% are risky. Thus, decision-makers should make detailed evaluations using robust, powerful, and practical decision-making tools to make more reasonable and logical decisions concerning country selection. Originality/value The current paper proposes a novel decision-making approach to evaluate. According to the authors' information, the proposed model has been applied to evaluate investable countries for the global supply chains for the first time.
Citation Count: 9
The potentials of the Southern & Eastern European countries in the process of the regionalization of the global supply chains using a q-rung orthopair fuzzy-based integrated decision-making approach
(Pergamon-Elsevier Science Ltd, 2022) Görçün, Ömer Faruk; Krishankumar, Raghunathan; Pamucar, Dragan; Gorcun, Omer Faruk
Recent challenges such as COVID 19 and the blockage of the Suez Channel have shown that the global supply chains (GSC) have extremely fragile structures. Hence, the GSCs have started to seek new strategies to be less affected. From this perspective, regionalization of the GSCs may be the best and most practical way to create more strength, well-operating, and robust supply chain systems. When a detailed literature review was per-formed, two severe and significant gaps were noticed. First is related to the methodological frame. The second gap is also concerned to the criteria used in the previous studies, as it is not clear how these criteria were identified and whether these criteria are suitable to the current real-life decision-making problems. The current paper aims to fill these gaps existing in the literatures. It examines the regionalization potentials of the GSCs and proposes an integrated MCDM framework based on the q-rung orthopair fuzzy sets. Also, it presents updated criteria set that can be commonly accepted. These criteria were identified by performing comprehensive field-work with highly experienced professionals with extensive knowledge of the GSCs and a detailed literature re-view to determine the criteria used in the previous works. The proposed model was applied to evaluate the potential of the southern and eastern European countries to be a manufacturing center for the GSCs. Then, a comprehensive sensitivity analysis performed for validating the proposed MCDM approach approves the pro-posed model's validity and efficacy by showcasing the close combat among the European countries.
Citation Count: 0
Prioritization of crowdsourcing models for last-mile delivery using fuzzy Sugeno-Weber framework
(Pergamon-elsevier Science Ltd, 2024) Görçün, Ömer Faruk; Lazarevic, Dragan; Dobrodolac, Momcilo; Simic, Vladimir; Gorcun, Omer Faruk
Modern technologies provide new opportunities for the industry but raise the expectations of the customers as well. This is valid also for the postal, courier, and logistics industries. The biggest challenge for the companies in the field is to improve the efficiency of the final phase in the transfer of shipments - last-mile delivery. A contemporary solution relates to collaboration between delivery companies and citizens who are willing to perform the delivery tasks as an additional activity to their established job or routine. Such a concept is known as crowdsourcing. There are several approaches within crowdsourcing, for example, transportation by car, utilizing public transport, etc. To make an appropriate choice, multiple criteria should be considered. This paper aims to propose an original methodology for solving the explained multi-criteria decision-making problem. The proposed framework is based on the application of the Sugeno-Weber nonlinear functions in a fuzzy environment. The application of the fuzzy Sugeno-Weber weighted assessment methodology showed that the proposed methodology has adaptability, a high degree of generalization, and stability of results. This enables the applicability of the methodology to various tasks from a broad spectrum of areas, which represents an additional value. A reallife case study is provided to solve the prioritization of crowdsourcing models in suburban municipalities of Belgrade, Serbia. The available alternatives and the most important criteria for the crowdsourced delivery model are identified. All criteria are divided into four groups, which define the dimensions of sustainability, including the technical aspect. The results of the conducted research indicate a high level of convenience in using one's car or daily bus lines for crowdsourced delivery to optimize the entire process of shipment transfer in the observed territory.
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.