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    EOQ model with transportation cost under deterministic demand
    (Işık Üniversitesi, 2012-12-24) Kars, Cihan; Altunbay, Seyhun; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Endüstri Mühendisliği - Yöneylem Araştırması Yüksek Lisans Programı
    Inventory planning issues are one of the most important aspects of the companies. To have optimal stock level both for production planning and low stock holding cost with successful demand forecast is also very important. If the companies work with high stock level, it causes the increase of the unused capital and it hinders to use the money for more effective operations. In global world, the companies purchase goods, semi-finished goods or materials from different regions of the world. They purchase the goods with variable quantities from different regions and directly affect the stock level of the companies. Furthermore it is essential to take transportation cost into account with the consumption quantity of material and the purchase price of unit material while determining inventory stock levels. There are also different payment options in purchasing of materials. The cash payment or the payment after receiving goods have also role in determining stock levels. When we take into account the transportation options and the payment options of purchasing materials the classical economic order quantity model is inadequate. The aim of this thesis is to have a new approach of economic order quantity model by considering the transportation cost and different payment options when we have deterministic demand. By the calculation of all possible transportation and payment alternatives, it becomes possible to find the optimum options of transportation and payment. The new model was implemented for a specific material of company X, for deterministic demand and the aim is to have optimal stock level for the specific material. The program MINITAB is used to find the appropriate method among different forecasting methods. The consumption of specific materials is evaluated and a sample group is composed to implement the new model. The all possible transportation modes, transportation durations and the historical demand data of 2010 and 2011 are collected and analyzed. Demand forecasting methods are applied on historical demand data and the results are accepted as deterministic and transportation modes and times are investigated in excel and used in problem. The process of the model is shown for the material WTR910R and the results are compared with the old system of company X.