Yazar "Boltürk, Eda" seçeneğine göre listele

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    Bulanık ortamda topsis yöntemi ile tedarikçi seçimi: bankacılık sektöründe bir uygulama
    (Yıldız Teknik Üniversitesi, 2015) Ayvaz, Berk; Boltürk, Eda; Kaçtıoğlu, Sibkat
    Evaluation and selection of the appropriate supplier is complicated and time consuming decision making process for companies. Selection of inappropriate supplier leds to higher cost and it influences negatively business process of companies in competitive environment. In this paper, fuzzy-TOPSIS method, considering combination of quantitative and qualitative evaluation criteria, is presented to select appropriate supplier under uncertain environment. The proposed model is applied to the electronic signature purchasing process of a firm that operates in banking sector in Turkey. Quality, purchasing costs, additional costs (maintenance, training, and update costs etc.), security level, compatibility with existing IT infrastructure, after-sales support, and technical competence are selected for supplier selection process in accordance with a detailed literature review and experts’ opinions.
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    Electricity consumption forecasting using fuzzy time series
    (2012) Boltürk, Eda; Öztayşi, Başar; Uçal Sarı, İrem
    Electricity is an important issue in energy management. Because of characteristic of electricity's non-storability, management of electricity is very valuable process. In this study, a Turkish company's two years electricity consumption have examined in order to predict possible electricity consumption. We used fuzzy time series with Singh's Method. Further, with the same data we compared total values of three periods (Unified consumption amount) and total consumption forecasts with their actuals. Finally we decide that which way is more accurate with root-mean-square deviation evaluation. © 2012 IEEE.
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    A grey system for the forecasting of return product quantity in recycling network
    (ExcelingTech Publishers, 2014) Ayvaz, Berk; Boltürk, Eda; Kaçtıoğlu, Sibkat
    In recent years, Reverse Logistics (RL) activities has gained much attention in terms of economic, social and governmental reasons. For firms, it has become important to manage the reverse flow of products in an efficient way to obtain competitive advantage. However to design RL network is difficult because of some reasons. Especially, uncertain parameters related to return product quantity, quality and time are main characteristics of RL networks. One of the most important decisions of RL is to provide a correct and timely estimation of return waste product quantity, because it affects many decisions related to RL network design process directly. To predict return product in RL networks, intrinsic and extrinsic forecasting are some of the well-known and frequently used forecasting techniques. In this study, we proposed a grey forecasting system to forecast return product quantity in RL network. The contribution of this study is the first study that presented grey forecasting model for product return quantity in reverse logistics network design literature. Solutions showed that grey forecasting system is very efficient to predict return quantity.
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    Proposed of a grey system for return WEEE product quantity forecasting in reverse logistics network
    (ETM, 2014) Ayvaz, Berk; Boltürk, Eda; Kaçtıoğlu, Sibkat
    Reverse Logistics (RL) has gained much attention in recent years due to economic, social and governmental reasons. For firms, it has become essential to manage the reverse flow of materials in an efficient way to gain competitive advantage. One important aspect of RL is to provide a correct and timely estimation of return waste product quantity. Improved forecast accuracy leads to a better decision making in strategic, tactic and operational areas of an organization. Intrinsic and extrinsic forecasting are some of the well-known and frequently used forecasting techniques to predict return product in RL networks. In this study, we presented a grey forecasting system to predict return waste product quantity in RL network. To the best of our knowledge, this study is the first in return product forecasting literature by using grey system to predict return quantity. Solutions showed that grey forecasting system is very efficient to predict return quantity.
  • Küçük Resim Yok
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    Risk assessment due to electricity demand forecasting under uncertainty
    (2013) Boltürk, Eda; Öztayşi, Başar
    With the new regulations in Turkey, companies have started to buy electricity from different suppliers in the market. Thus, from the perspective of the electricity providers demand forecasting has become a significant issue. Errors in electricity demand forecasting generate a considerable amount of risk. For electricity suppliers, assessment of this risk caused by the uncertainty has become an important issue. In this paper real world case study is given and Value-At-Risk (VAR) value is calculated due to load forecast errors. The ARIMA and Grey forecasting methods are used for predicting the electricity consumption. © 2013 Taylor & Francis Group.