Kompleks tedarik zinciri aglarinin modelleme, cozum ve uygulamalari

In this thesis, the main focus is the supply chain networks in terms of modeling, solution and applications. Networks are one of the main representation tools for the systems in engineering, science and management. Supply chain networks are the specific networks that are used to represent the flows of materials, information and financials from one physical node to others. The supply chain context is very broad, we consider it in 3 parts: Modeling, solution and applications, during this thesis. In the modeling part the development of new modeling technique is described in detail. In conventional supply chain network modeling, the flows and the inventories are modeled separately for each flow and node. This makes modeling and re-modeling difficult to maintain. In this new modeling technique, the network topology that represents the flows, entities and inventories are stored in multi-dimensional matrix. Therefore model-data independence is succeeded. This makes models lean and easy to maintain. In the solution part, we have focused on the non-integer representation of the batch behaviors in the supply chain network. In conventional modeling, this batch behavior is modeled by using integer variables. However this makes the model combinatorial and difficult to solve. Therefore, in this thesis, we have developed new solutions techniques to model batch behavior without using integer variables. Finally, in applications part, we have developed a new version of the VRP (Vehicle Routing Problem). The capacities for this new version of the VRP show combinatorial behavior. A new algorithm is developed to solve this new VRP problem. It is known that VRP is one of the most difficult problems in the literature. With addition of new combinatorial capacity constraints, some models can become computationally intractable. With this new developed algorithm, the capacity constraints can be handled in polynomial time.