In today's world, the fact that information applications have become an indispensable part of life with the effect of the developments in information technologies has led to a huge rate of data production and usage. As a result of this, the need for data centers has increased. Although Turkey is a country with advantages that can play a leading role in the field of data centers in the region where it is located, it has some disadvantages too. Some of these disadvantages are natural disasters index, climate index, energy index, accessibility index, human capital and quality of life index (HCLQ). In this context, these disadvantages are considered as criteria for data center location selection problem. In this study, criteria weights were determined by fuzzy DEMATEL (The Decision Making Trial and Evaluation Laboratory) method in the problem solving and alternatives (81 provinces) were ranked using EDAS (Evaluation based on Distance from Average Solution) method. According to the results, it was found that Istanbul is the best alternative in data center location selection.
In today's world, the fact that information applications have become an indispensable part of life with the effect of the developments in information technologies has led to a huge rate of data production and usage. As a result of this, the need for data centers has increased. Although Turkey is a country with advantages that can play a leading role in the field of data centers in the region where it is located, it has some disadvantages too. Some of these disadvantages are natural disasters index, climate index, energy index, accessibility index, human capital and quality of life index (HCLQ). In this context, these disadvantages are considered as criteria for data center location selection problem. In this study, criteria weights were determined by fuzzy DEMATEL (The Decision Making Trial and Evaluation Laboratory) method in the problem solving and alternatives (81 provinces) were ranked using EDAS (Evaluation based on Distance from Average Solution) method. According to the results, it was found that Istanbul is the best alternative in data center location selection.
Demand forecasting is a difficult field of study for intermittent demands. Spare parts demand structures also have an intermittent demand structure. Therefore, for companies operating in this field, this situation causes various problems (holding cost or cost of lost sale). Intermittent demands are inherently difficult to predict. Demands with a smooth structure provide a more suitable working environment for businesses. Because the more accurately the relevant demand is forecasted, the more smoothly the works that depend on demand forecasting are carried on. In this study, a randomly generated demand series with intermittent demand structure is examined. The estimation difficulty of intermittent demand is illustrated by an estimation made in Matlab. In order to avoid this difficulty, the costs were tried to be minimized by determining the inventory levels. An inventory model is proposed that determines stock levels using intermittent demands and calculates average profit by calculating costs. The related model was solved with Genetic Algorithm in Matlab and the results were recorded.
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