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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 GREY MCDM MODEL: CASE OF WAREHOUSE LOCATION SELECTION
    (Univ Nis, 2021) Ulutas, Alptekin; Balo, Figen; Sua, Lutfu; Demir, Ezgi; Topal, Ayse; Jakovljevic, Vladimir
    Warehouses link suppliers and customers throughout the entire supply chain. The location of the warehouse has a significant impact on the logistics process. Even though all other warehouse activities are successful, if the product dispatched from the warehouse fails to meet the customer needs in time, the company may face with the risk of losing customers. This affects the performance of the whole supply chain therefore the choice of warehouse location is an important decision problem. This problem is a multicriteria decision-making (MCDM) problem since it involves many criteria and alternatives in the selection process. This study proposes an integrated grey MCDM model including grey preference selection index (GPSI) and grey proximity indexed value (GPIV) to determine the most appropriate warehouse location for a supermarket. This study aims to make three contributions to the literature. PSI and PIV methods combined with grey theory will be introduced for the first time in the literature. In addition, GPSI and GPIV methods will be combined and used to select the best warehouse location. In this study, the performances of five warehouse location alternatives were assessed with twelve criteria. Location 4 is found as the best alternative in GPIV. The GPIV results were compared with other grey MCDM methods, and it was found that GPIV method is reliable. It has been determined from the sensitivity analysis that the change in criteria weights causes a change in the ranking of the locations therefore GPIV method was found to be sensitive to the change in criteria weights.
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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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    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.