Servis ve üretim sistemleri için esneklik yapısı tasarımı ve kapasite eniyilemesi

In this thesis, we analyze the capacity optimization problem with an objective ofmaximizing the profit in a multi-resource system under uncertain demand. For any realizationof demand, the optimal capacity level is a function of the flexibility structure, the capacitycost and the prices. However, for unknown demand, the problem becomes more complicated.We solve the problem as a two-stage stochastic optimization problem. In the first stage,capacities are determined prior to the realization of demand. In the second stage, the realizeddemand is allocated to the resources. We propose and test a solution method based on thegradient estimation via perturbation analysis (GPA) technique. Our method is a simulation-based optimization procedure. After analyzing the legitimacy of the method through itstheoretical properties, we apply the method to a few benchmark cases and confirm theaccuracy of the method via numerical examples. Then we perform a numerical study toexplore the link between capacity optimization and flexibility design considering the cost ofthe capacity. Despite the fact that literature asserts the advantage of the balanced flexibilitystructure, we show that through optimizing the capacity, some imbalanced structures canperform better in some cases.