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    Criteria for selection of transportation vehicles according to cargo companies using fuzzy methods
    (IGI Global, 2021) Topal, Ayşe; Yürüyen, Ali Aygün; Ulutaş, Alptekin; Karabasevic, Darjan; Karaköy, Çağatay
    Freight transportation is one of the most important and costly operations in logistics as economy and society are significantly depended on freight transportation for the sustainability of life. Vehicle selection in freight transportation is a crucial and strategic decision as it requires high investments, and if the desired performance cannot be achieved from these vehicles, which were bought at a high expense, they would inevitably be idle. Vehicle selection problem in logistics is essentially a multi-criteria decision problem as it consists of several criteria, some conflicting with each other. The aim of this research is to find out which criteria freight companies value the most when assessing and selecting the vehicles they use on the road by using fuzzy BWM and fuzzy SWARA methods. Since the number of studies using fuzzy BWM and fuzzy SWARA is low in the literature and there are few studies in the literature related to transportation vehicle selection in the logistics, this study will contribute to the literature. © 2021, IGI Global.
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    A new integrated grey mcdm model : Case of warehouse location selection
    (Faculty of Mechanical Engineering, 2021) Ulutaş, Alptekin; Balo, Figen; Sua, Lutfu; Demir, Ezgi; Topal, Ayşe; Jakovljević, 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