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    A Novel Grey MCDM Model Assessing Macroeconomic Performance of G7 Countries
    (Research Information Ltd, 2025) Ulutas, Alptekin; Topal, Ayse; Karabasevic, Darjan; Zavadskas, Edmundas Kazimeras; Demirbas, Muzaffer; Ure, Salim
    Macroeconomic indicators offer critical insights into the economic performance of nations. The potential variability of these factors necessitates formulating policies and implementing actions to counteract any adverse situations that may arise. This research aims to evaluate the macroeconomic performances of the seven developed nations, known as the G7 nations. The research identified imports of goods and services, exports of goods and services, gross fixed capital formation, gross domestic savings, unemployment, population, current account balance, inflation, consumer prices gross domestic product as criteria for performance assessment. An integrated framework integrating the LOPCOW-G and RAWEC-G methodologies is presented to assess the macroeconomic performance of G7 nations within the study's framework. The weight values derived from the LOPCOW-G technique indicate that the current account balance is the most significant factor influencing macroeconomic success. The RAWEC-G technique findings indicate that Japan had the highest economic performance, while the USA demonstrated the lowest economic performance.
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    Energy-Performance Evaluation with Revit Analysis of Mathematical-Model-Based Optimal Insulation Thickness
    (Mdpi, 2023) Balo, Figen; Ulutas, Alptekin
    This study investigates the optimum insulation thickness value using MATLAB Optimization Toolbox based on a mathematical model for sandwich walls that are formed with different insulation-building materials by different fuel types for a particular city located in the second climatic region of Turkey. In the second stage of study, using the BIM-based Revit simulation program, a building was designed with the same building-insulation materials under the same climate conditions. The six different wall performances were compared for the designed building. The study proposes a comprehensive approach by combining technical and economic factors in the sustainable design of buildings. The computational results indicate that using different energy alternatives has a significant impact on the air quality in residential areas. The lowest value is reached when natural gas is used. The energy cost savings change from 7.56 to 14.12 TRY/m(2) for external walls. While payback periods vary between 2.15 and 3.76 years for external walls, the lowest period for all wall types is obtained for electricity, which has a high cost. The optimum insulation thickness for 10 years of lifetime varies between 0.02 and 0.16 m. This study reflects that the highest optimal insulating thickness is reached when electricity is utilized as the energy source for all wall types. According to the Revit analysis, the lowest energy consumption of 21,677 kWh during one year using natural gas was obtained for a building material of porous light brick and an insulation material of glass wool.
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    Environmental considerations in the selection of transport vehicles: a fuzzy FUCOM method
    (Emerald Group Publishing Ltd, 2025) Yuruyen, Ali Aygun; Ulutas, Alptekin; Demirhan, Azize; Ozsalman, Emre
    PurposeBusinesses are starting to prioritize environmental concerns more when conducting their operations due to increasing awareness of environmental degradation and legal obligations. Thus, companies must take into account a variety of factors when buying the equipment that they need to carry out their operations. More importantly, these factors need to be properly considered because buying a vehicle is a costly decision.Design/methodology/approachThe study was conducted in a logistics company operating in Ankara. The data collected were obtained from five experts working as senior managers in this logistics company using an e-mail survey method, one of the modern survey types. In the study, a mixed decision-making approach based on subjective criteria expressed linguistically in an environment of uncertainty was adopted, and fuzzy full consistency method (F-FUCOM) was used to prioritize criteria by integrating environmental factors into the criteria that logistics companies take into account when selecting transportation vehicles. In total, 4 main and 17 sub-criteria were evaluated according to the decision-makers' perspectives.FindingsThe study's result shows that the main criterion with the highest importance was environmental, while the main criterion with the lowest importance was cost. Furthermore, vehicle life was found to be the most important sub-criterion, which is one of the environmental main criteria, while the vehicle's net weight was found to be the least important sub-criterion, which is one of the equipment main criteria.Originality/valueThe role of environmental criteria and multi-criteria decision-making approaches in transportation vehicle selection remains underexplored in the literature. Moreover, the F-FUCOM approach has not been applied to such complex problems. This study addresses these gaps by incorporating environmental factors into a comprehensive methodological framework, advancing both theory and practice in the field.
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    THE EVALUATION OF ECONOMIC FREEDOM INDEXES OF EU COUNTRIES WITH A GREY HYBRID MCDM MODEL
    (Inst Economic Forecasting, 2023) Karakoy, Cagatay; Ulutas, Alptekin; Karabasevic, Darjan; Ure, Salim; Bayrakcil, Ali Oguz
    The Economic Freedom Index is a valuable comparison tool in terms of helping countries to consider in which areas they are better and determining priorities accordingly, as well as ensuring full economic freedom. There are many studies in the literature on this index. However, no study that deals with the criteria of the economic freedom index with grey MCDM methods has been found in the literature. In this study, the 5-year (2018-2022) economic freedom sub-criteria of 27 countries that are members of the European Union are handled with Grey PSI and WEDBA-G methods. This study has two contributions to the literature. First, a new grey MCDM method, called the WEDBA-G method, was developed. Second, a new grey hybrid model including grey PSI and grey WEDBA is presented.
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    Evaluation of third-party logistics service providers for car manufacturing firms using a novel integrated grey LOPCOW-PSI-MACONT model
    (Pergamon-Elsevier Science Ltd, 2024) Ulutas, Alptekin; Topal, Ayse; Gorcun, Omer Faruk; Ecer, Fatih
    Automotive businesses often delegate logistical tasks to third-party logistics (3PLs) service providers to acquire a competitive edge in the dynamic market. Nevertheless, selecting the most suitable third-party logistics (3PL) partner is a multifaceted undertaking that needs careful evaluation of several criteria and alternatives. This research aims to introduce an integrated grey Multiple Criteria Decision Making (MCDM) framework for automotive businesses to deal with the multidimensional 3PL selection decision problem. This framework incorporates an enhanced Preference Selection Index (PSI), Logarithmic Percentage Change-driven Objective Weighting (LOPCOW), and Mixed Aggregation by Comprehensive Normalization Technique (MACONT). The LOPCOW-G and grey PSI (PSI-G) methods extract the criterion weights, whereas the MACONT-G method ranks the alternatives. The suggested framework's practicality is shown by conducting a case study about evaluating and selecting a third-party logistics (3PLs) provider. The findings indicate that the parameters of significant importance are skilled workforce (0.0977), financial strength (0.0901), and IT-IS competence (0.0839). Furthermore, TPL4 has been recognized as the most optimum option with a value of 0.4797. The MACONT-G model is as well compared against other grey MCDM techniques to assess the validity of the proposed model. The Pearson correlation coefficient between MACONT-G and the other models based on grey sets is 0.958, suggesting a significant and positive link. Furthermore, it is worth noting that a sensitivity analysis has been conducted to validate the accuracy and reliability of the created framework. In conclusion, this study has identified managerial and policy implications that might assist policymakers and executives in effectively evaluating 3PL providers.
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    Fermatean fuzzy framework based on preference selection index and combined compromise solution methods for green supplier selection in textile industry
    (Taylor & Francis Ltd, 2024) Pamucar, Dragan; Ulutas, Alptekin; Topal, Ayse; Karamasa, Caglar; Ecer, Fatih
    This work aims to enhance the efficiency and dependability of the green supplier selection process by developing a decision support tool. Thereby, a novel fuzzy group multi-criteria decision-making approach based on the Preference Selection Index (PSI) and Combined Compromise Solution (CoCoSo) methods under the Fermatean Fuzzy (FF) environment for green supplier selection is proposed. The primary novelties and contributions are: (i) for the first time, the FF-PSI model is developed to extract the priority weight values of criteria, (ii) an improved FF-CoCoSo methodology is proposed, and (ii) the FF-PSI-CoCoSo framework is offered for resolving challenging real-life problems. To present the framework's practicality, a real-case study evaluating six suppliers concerning nine drives under economics, environmental, and technological aspects in a textile company in Turkey is conducted. The results indicate that green warehousing is the most essential driver for green suppliers, followed by recycling and damaged product ratio. A detailed sensitivity and comparison check is further conducted to display the solidity and effectiveness of the proposed framework. The suggested framework offers a reliable solution for green supplier selection and a precise sustainable rating of suppliers. Moreover, it can be addressed to solve various challenging real-world problems.
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    Green-resilient supplier selection via a new integrated rough multi-criteria framework
    (Elsevier, 2025) Ulutas, Alptekin; Topal, Ayse; Ecer, Fatih
    Initially, companies focused solely on the economic aspects of business processes; now, they have begun to prioritize environmental and social issues to mitigate adverse impacts on the ecology and community. Furthermore, resilience is crucial in ensuring the supply chain remains uninterrupted. Therefore, evaluating the suppliers' sustainability and resilience performance is paramount. A unique mathematical tool is required to integrate resilience and sustainability considerations into supplier selection decisions. Hence, the research fulfills this necessity by introducing a novel, multi-criteria rough methodology. The studies in the literature primarily assess suppliers from either a green or resilient perspective, employing fuzzy MCDM methods to address uncertainty. However, they struggle to cope with uncertainty when faced with limited information. To address this gap, this study proposes a novel approach based on rough set theory to handle interpersonal ambiguity and vagueness flexibly without requiring additional information. It determines the weights of criteria used for greenresilient supplier selection and evaluates the green-resilient performance of suppliers. To this end, rough logarithmic percentage change-driven objective weighting and rough maximum of criterion frameworks are developed to determine criteria weights, whereas the rough mixed aggregation by the comprehensive normalization technique model is designed to decide alternative rankings. This approach requires less prior information than fuzzy set-based methodologies and offers additional flexibility in handling imprecision. To demonstrate its practicality, a real case study from a garment-textile factory in Turkey is presented. The work is the first study of this issue to employ the introduced methodology. Findings highlight that the impact on the local community is the foremost driver for green-resilient supplier selection, followed by cost and supplier sustainability. The model's reliability is validated by comparative and sensitivity analysis. The research contributes to the field by providing a reliable tool that combines rough sets with resilience and sustainability approaches, thus improving the effectiveness and credibility of supplier selection activities in engineering. The work provides executives with an effective supplier evaluation process that jointly addresses sustainability and resilience assessments under uncertainty.
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    HYBRID REVIT AND A NEW MCDM APPROACH OF ENERGY EFFECTIVE NURSING-HOME DESIGNED BY NATURAL STONE AND GREEN INSULATION MATERIALS
    (Vilnius Gediminas Tech Univ, 2025) Balo, Figen; Ulutas, Alptekin; Stevic, Zeljko; Boydak, Hazal; Zavadskas, Edmundas Kazimieras
    The requisition for maintainable constructions has been greatly raising over the last several years. To fulfil the maintainability necessities of a construction, decisions or changes must be done to a construction in the course of the preconstruction and design steps. This can be plausible utilizing building information modelling. To indicate the utilize of building information modelling in maintainable planning, an example nursing-house is received for modelling research. The energy efficiency of nursing-home is analysed utilizing Autodesk Revit and Green Building Studio simulation which contained different characteristics such as annual heating and cooling loads, annual energy usage. Through using the utilize of different building, insulation and roof materials in the nursing-home modelling, the nursing-home modelling is changed into a greener construction modelling. In addition, the effects of using green walls on the facade of the building on the energy performance were analysed. Utilizing simulation, the utilize of non-natural sources can be dramatically decreased through substituting for them with the utilize of sustainable natural sources by that means energy saving. Building information modelling has substantiated to be effective in providing maintainability with alternative material's assessment and earlier decision-making. Furthermore, this study employed an integrated new MCDM model to evaluate the performance of four natural stones for utilize in a nursing home setting.
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    Identifying the Most Efficient Natural Fibre for Common Commercial Building Insulation Materials with an Integrated PSI, MEREC, LOPCOW and MCRAT Model
    (Mdpi, 2023) Ulutas, Alptekin; Balo, Figen; Topal, Ayse
    Building insulation is the most respected among the compatible and effective energy conservation technologies available today, as it also reduces yearly energy costs and negative environmental effects. A building envelope is made up of various insulation materials that are important in determining a building's thermal performance. Proper insulation material selection concludes in less energy requisition for operation. The purpose of this research is to supply information about natural fibre insulating materials used in construction insulation to maintain energy efficiency, as well as to recommend the most efficient natural fibre insulation material. As in most decision-making problems, several criteria and alternatives are involved in insulation material selection, too. Therefore, we used a novel integrated multi criteria decision making (MCDM) model including the preference selection index (PSI), method based on the removal effects of criteria (MEREC), logarithmic percentage change-driven objective weighting (LOPCOW), and multiple criteria ranking by alternative trace (MCRAT) methods to deal with the complexity of numerous criteria and alternatives. The contribution of this study is that a new hybrid MCDM method is developed. Additionally, the number of studies using the MCRAT method is very limited in the literature; therefore, this study will provide more insights into and results of this method to the literature.
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    MCDM MODEL FOR CRITICAL SELECTION OF BUILDING AND INSULATION MATERIALS FOR OPTIMISING ENERGY USAGE AND ENVIRONMENTAL EFFECT IN PRODUCTION FOCUS
    (Vilnius Gediminas Tech Univ, 2023) Ulutas, Alptekin; Balo, Figen; Mirkovic, Katarina; Stevic, Zeljko; Mostafa, Mohamed M. H.
    In the context of sustainable buildings, an ecological study of building and insulating materials is critical since it may assist affirm or shift the path of new technology development. Utilising sustainable material is a part of the sustainable improvement. For this reason, material fabrication is the primary process for the energy usage and release of intense environmental gaseous. The fabrication of the insulation and building materials, as in every fabrication process, comprises an energy consumption of crude materials in addition to the pollutants' release. In buildings, insulation is a relevant technological resolution for cutting energy usage. This study aims to assess the primary energy consumption and the environmental effects of the fabrication of building and thermal isolation materials by using a new hybrid MCDM model. The proposed new hybrid MCDM model includes Fuzzy FUCOM, CCSD and CRADIS methods. While the subjective weights of the criteria were determined with the fuzzy FUCOM method, the objective weights of the criteria were determined with the CCSD method. Construction materials were listed with the CRADIS method. According to the fuzzy FUCOM method, the most important criterion was determined as the CR3 criterion, while the most important criterion according to the CCSD method was determined as the CR1 criterion. According to the combined weights, the most important criterion was determined as the CR3 criterion. According to the CRADIS method, the material with the best performance was determined as Cement Plaster. The methodology used in this study is a novel approach therefore it has not been used in any study before. In addition, since the CRADIS method is a newly developed MCDM method, the number of articles related to this method is low. Therefore, this research gap will be filled with this study.
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    MULTIPLE NORMALIZATION RATING ANALYSIS (MUNRA) AND ITS APPLICATION TO DIGITAL SUPPLIER SELECTION IN THE TEXTILE INDUSTRY
    (Vilnius Gediminas Tech Univ, 2025) Ulutas, Alptekin; Ecer, Fatih; Turskis, Zenonas
    The rapid development of digital technologies-such as IoT, AI, blockchain, and digital twins-has transformed supply chains into interconnected ecosystems, making digital supplier selection both critical and complex. For the first time, this study proposes a novel multi-criteria decision-making (MCDM) method, Multiple Normalization Rating Analysis (MUNRA), for ranking alternatives. It integrates linear, vector, and non-linear normalization to improve robustness, reduce rank reversal, and enhance decision accuracy. A case study of digital supplier selection in the textile industry is considered for a real-life application of the method. Results highlight technology integration, flexibility, and technological capability as the most influential criteria for selecting digital suppliers. Moreover, the final ranking of the six digital suppliers is as follows: DS5, DS4, DS2, DS6, DS1, and DS3. Validation through comparative MCDM methods, Spearman correlation, and sensitivity analyses confirms the credibility of the method. It is also shown that it is free from the rank reversal phenomenon. The research presents a computationally efficient and rigorous method for evaluating digital suppliers, offering strategic insights for digital supply chain management. The application of MUNRA to a larger decision-making problem further illustrates its scalability and cross-domain applicability.
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    A New Fuzzy Stochastic Integrated Model for Evaluation and Selection of Suppliers
    (Mdpi, 2023) Ulutas, Alptekin; Kiridena, Senevi; Shukla, Nagesh; Topal, Ayse
    In light of the rapid rate of change and unforeseen occurrences seen in the realms of technology, market dynamics, and the wider business landscape, there is a growing need for the inclusion of uncertainty and risk factors in the realm of supply chain planning. Supplier evaluation and selection (SES) is a major strategic decision area where the impact of uncertainty and risk can be more proactively dealt with. A review of extant literature reveals that there is a strong need for developing practitioner-oriented and more comprehensive frameworks and models to mitigate both the capability- and performance-related risks, in the context of SES decisions. This paper presents an integrated model to support SES decisions involving quantity discounts and multiple planning periods under stochastic conditions. The proposed model employs the Fuzzy Analytical Hierarchy Process (FAHP), Fuzzy Evaluation Based on Distance from Average Solution EDAS (EDAS-F), and fuzzy stochastic goal programming (FSGP) to effectively address the above requirements. A case study from a garment manufacturing industry is used to demonstrate the efficacy of the proposed model. The findings of the study provide confirmation that the suggested FSIM has the ability to provide substantial advantages in the context of making choices related to quantity discounts in SES. The proposed FSIM model incorporates the use of FAHP and EDAS-F techniques to effectively reduce the number of suppliers to a manageable level, taking into consideration capability-based risks. Additionally, fuzzy stochastic goal programming (FSGP) is employed to mitigate performance-based risks, enabling the selection of suppliers and the allocation of orders among them. The paper contributes to the literature by proposing a comprehensive framework to solve the SES problem, considering certain practical situations faced by organizations.
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    A new hybrid MCDM method for optimizing natural stone selection for building envelopes
    (Pontificia Univ Catolica Chile, Escuela Construccion Civil, 2023) Ulutas, Alptekin; Balo, Figen; Topal, Ayse
    Most kinds of natural stones are perfect coating materials. Through utilizing stones with less thermal conduc-tivity coefficients, isolation of constructions improves with energy effective resolution. Modern building technologies prefer either decreasing stone to the weakest plausible extents or utilizing natural stones because natural stones have lower thermal conductivity with lighter weights. For this reason, first, the thermal and physical characteristics of natural stones used as coating material on the exterior walls of the buildings were investigated in this study. Then, in the light of these characteristics, natural stones with the best performance in terms of energy efficiency were determined using multi-criteria decision-making methods including FFSWARA and COBRA. The findings show that compressive strength is the most significant criteria and Isparta andesite stone is the most superior natural stone in terms of performance. This study con-tributes to the literature in three ways. First, the COBRA method used in this study has recently been introduced to the literature. Therefore, it has not been covered much in the literature. Second, this method has not been used in the selection of natural stone selection in the literature to our best knowledge. Third, this method has not been used together with the FFSWARA method before.
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    A New Integrated Multi-Criteria Decision-Making Model for Sustainable Supplier Selection Based on a Novel Grey WISP and Grey BWM Methods
    (Mdpi, 2022) Ulutas, Alptekin; Topal, Ayse; Pamucar, Dragan; Stevic, Zeljko; Karabasevic, Darjan; Popovic, Gabrijela
    Supplier selection is an important task in supply chain management, as suppliers have a vital role in the success of organisations in a supply chain. Sustainability has emerged as a solution to decreasing resources and increasing environmental and social problems in the past few decades. It has been applied to various industrial operations, one of them is supplier selection, to mitigate unwanted effects in the future. Sustainable supplier selection is a complicated multi-criteria decision making problem, including several criteria from economic, environmental, and social perspectives. To deal with subjective judgements of decision makers, fuzzy and grey methods are widely used in multi-criteria decision making, In the case of small, limited, and incomplete data, the grey theory provides satisfactory results, compared to fuzzy methods. Therefore, this study is an integrated method including grey Best-Worst Method (BWM) and grey Weighted Sum-Product (WISP) for choosing the most sustainable supplier for a textile manufacturer, which includes three main criteria and twelve sub-criteria. According to the result of the proposed model, the supplier with the best performance was determined to be the supplier with the SP2 coded. The results of the developed model were shown to the experts, and the accuracy of the results was confirmed. According to the experts, a higher amount of product can be purchased from the supplier with the SP2 code, and a tighter relationship can be worked with this supplier. The contributions of this study are: (1) Develop a new grey MCDM model called Grey WISP. (2) Create a new integrated MCDM model with grey theory, BWM, and WISP methods that can be applied to assess supplier sustainability using this hybrid model. The proposed model can be used not just for selecting sustainable suppliers, but also for any other decision problems that have multiple criteria and alternatives. The findings suggest that the Grey WISP method achieved accurate results.
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    A Novel Hybrid Gray MCDM Model for Resilient Supplier Selection Problem
    (Mdpi, 2024) Ulutas, Alptekin; Krstic, Mladen; Topal, Ayse; Agnusdei, Leonardo; Tadic, Snezana; Miglietta, Pier Paolo
    The current business climate has generated considerable uncertainty and disrupted supply chain processes. Suppliers have frequently been identified as the primary source of hazards responsible for supply chain disruptions. Using a strategic approach to supplier selection that prioritizes providers with resilience features, mitigating the risk exposure inherent in supply chains is possible. This study proposes a comprehensive gray multiple-criteria decision making (MCDM) method incorporating resilience attributes to supplier selection. To determine criteria weights, the gray PSI and gray BWM methodologies were used, and to evaluate and prioritize resilient providers, the gray MCRAT and gray COBRA methodologies were applied. According to the results obtained by the suggested methodology, the supplier that demonstrated the greatest degree of resilience was determined to be the provider categorized as SPIR 4. The sequential sequence of the SPIR numbers is as follows: SPIR 5, SPIR 1, SPIR 3, SPIR 2, and SPIR 6. The data demonstrate that the developed approach produced accurate results.
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    Optimal Configuration of Spatial Planning for Energy-Efficient Buildings
    (Univ North, 2024) Balo, Figen; Ivanovic, Biljana; Stevic, Zeljko; Ulutas, Alptekin; Marinkovic, Dragan; Demir, Hazal Boydak
    The project phase is where the life-cycle of a building starts. The best decisions are made during the design or pre-project step. In terms of both economic resources and time, changes to specific design decisions made at this step are inexpensive compared to subsequent steps of architectural planning, not to mention the course of the construction's operation itself. The choices made during the design phase determine to a large extent whether the architectural design decisions ofa building are achieved, whether the building and site can be used appropriately, and whether the project is economically viable. With BIM, building spatial planning is possible. As a result, architects can evaluate the proposed structure, its impact on the ecology, and the ecology's impact on the structure more comprehensively and at an earlier stage. This research proposes an energy modeling approach for the BIM-based spatial planning phase of a construction. The proposed method will result in an energy model for specific sites and building resolutions when utilized to create a spatial modelling for a construction. The energy model can then be used for new architectural creations. In this study, 36 different alternative scenarios were designed in terms of the rate of construction height to construction spacing, orientation factor, and form factor. With the help of BIM and GBS softwares, the energy consumption values of the alternative scenarios in cooling and heating load conditions were compared, and the alternative scenario with the minimum energy consumption was tried to be determined with spatial planning parameters.
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    Selection of a Forklift for a Cargo Company with Fuzzy BWM and Fuzzy MCRAT Methods
    (Mdpi, 2023) Ulutas, Alptekin; Topal, Ayse; Karabasevic, Darjan; Balo, Figen
    Material handling is a cost-intensive operation for businesses. There are several alternative types of equipment for material handling, therefore it is important to select the best one among them to decrease the cost. As there are several different alternatives and criteria which are used to assess these alternatives, multi-criteria decision making (MCDM) techniques are useful to determine the optimal material handling equipment (MHE) for businesses. In this study, fuzzy BWM for determining weights of criteria and the fuzzy Multiple Criteria Ranking by Alternative Trace (MCRAT) method have been used for ranking forklift alternatives. This study's significance in the literature will be the creation of a novel fuzzy MCDM technique with the application of fuzzy MCRAT. Furthermore, there are relatively few studies employing the MCRAT approach in the literature; therefore, this study will provide additional data and outcomes from this method to the literature. The findings present that the forklift with the code FLT-3 performed the best, whereas the forklift with the code FLT-2 had the worst performance, according to the fuzzy MCRAT technique. According to the comparison analysis, the fuzzy MCRAT produced the same results as the fuzzy ARAS and had a few subtle differences to fuzzy MARCOS.
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    Selection of peanut butter machine by the integrated PSI-SV-MARCOS method
    (Ios Press, 2023) Toslak, Melike; Ulutas, Alptekin; Ure, Salim; Stevic, Zeljko
    Production enterprises are enterprises that produce goods or services that aim to meet human needs such as machinery-equipment materials and labour. In order for a manufacturing enterprise to carry out its activities successfully, it must make the right choice when choosing its inputs. The correct execution of production activities and the selection of machinery, which requires high capital investments, also affect the efficiency of the enterprises, the correct use of materials and their costs. Therefore, it is an important decision for business managers to choose the right machine. At this stage, multi-criteria decision making (MCDM) methods are used for choosing the right machine. MCDM methods are methods used in the evaluation of alternatives using more than one criterion. In addition, the MCDM method is used in machine selection as well as in many areas. In this study, PSI, SV and MARCOS methods, which are among the MCDM methods, were used for peanut butter machine selection. First, the criteria and alternatives to be used for the peanut butter machine selection were determined by interviewing a peanut butter factory manager. In the study, while the criteria weights were determined, PSI and SV methods were used, while the machines were ranked with the MARCOS method. In addition, the MARCOS method was compared with other MCDM methods such as PIV, CODAS and WEDBA methods. After the rankings were found according to the methods, the relations between the rankings were examined using the Spearman Correlation method. The main purpose of the study is to determine the suitable butter machine for a peanut paste production factory. Contribution of this study to the literature PSI, SV and MARCOS methods were used together for the first time. In addition, no study has been found in the literature related to peanut butter machine. Therefore, this study is original and contributes to the literature.
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    Simulation-Based Hybrid Analysis of Eco-Friendly Wall Coatings Using LODECI, MAXC and DEPART Methods for Energy-Efficient Buildings
    (Mdpi, 2025) Balo, Figen; Ulutas, Alptekin; Ari, Ilknur; Das, Dillip Kumar; Stevic, Zeljko
    Thermal insulation is essential in lowering the energy consumption of buildings. However, many fossil-based insulation and exterior cladding materials are derived from petrochemical components, which often have adverse ecological impacts. This study explores the effectiveness of integrating sustainable thermal insulation solutions into building design to reduce energy consumption and minimize ecological impact. Focusing on an energy-efficient breakfast house located in Van, Turkey, the project was modeled using Autodesk-Revit software (2023). A comprehensive analysis was conducted by generating eighty alternative scenarios, combining two distinct wall structures, eight fiber-based natural insulation materials, and five wood-based exterior cladding materials. The energy performance of each scenario was evaluated using IES-VE software (2024.1), focusing on annual total energy consumption and CO2 emissions, while accounting for regional climatic conditions and targeted indoor comfort levels. To further refine the selection of optimal materials, a hybrid evaluation was performed using multi-attribute decision approaches, including LODECI, MAXC, and DEPART. These methods provided a systematic framework for comparing the performance of wood-based insulation materials across multiple criteria. In order to verify the accuracy of the proposed multi-attribute decision models, a comparative analysis has been undertaken with other multi-attribute decision methods (COPRAS, ARAS and WASPAS). The study highlights the technical feasibility of incorporating cost-effective, eco-friendly fiber-based and wood-based materials into building envelopes, demonstrating their potential to significantly enhance energy efficiency and reduce environmental impact. By combining advanced simulation tools with robust decision-making methodologies, this research offers a scientifically grounded approach to sustainable architectural design, providing important outputs for future applications in energy-efficient construction.
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    Supply Chain Management (SCM) Breakdowns and SCM Strategy Selection during the COVID-19 Pandemic Using the Novel Rough MCDM Model
    (Wiley-Hindawi, 2023) Stevic, Zeljko; Ulutas, Alptekin; Korucuk, Selcuk; Memis, Salih; Demir, Ezgi; Topal, Ayse; Karamasa, Caglar
    Supply chain management (SCM) is deeply affected by the COVID-19 pandemic besides breakdowns occurred in all sectors. Nowadays, managers need techniques for protecting supply chains from serious and costly disruptions, establishing permanent relationships with the customers and partners and preventing breakdowns throughout the process. Each firm needs to determine SCM strategies to be prepared for breakdowns in an intense competitive environment. With COVID-19, the change in business and trade environments has taken a different dimension, and it has revealed a new relationship between the efforts to perpetuate supply chains and strategies for supply chain management and enabled new models. In this study, it is aimed to prioritize the factors that lead to SCM breaks needed in project management and the realization of projects, and to choose the most successful SCM strategy considering COVID-19. For this purpose, rough SWARA was used for weighting factors and rough MARCOS was used for the alternative selection. According to the findings, the transportation capacity factor was found to be the most important factor leading to SCM breakdowns. The most ideal supply chain management strategy has been the collaborative supply chain management strategy. In the food manufacturing sector, the study can be considered as a roadmap in terms of preventing supply chain management breaks during the COVID-19 process and helping to ensure a sustainable production. As another theoretical and practical importance of the study, it is aimed to propose a robust, powerful, and practical decision-making model that can cope with the current uncertainties.