Capacity constrained inventory management policies and a comparison of them

Inventory management under capacity constraint constitute some important sections of inventory management researches. It is one of methods that uses Lagrange relaxation to solve economic order quantity model under capacity constraint. Each order has different cycle time therefore they are distributed randomly over the time. Despite the random storage proposition in some researches, it is clear that dedicated storage assignment methods of capacity usage may cause inefficient usage of capacity. Assigning dedicated capacity usage in random storage situation, new capacity constraint are created and order quantities are calculated in different storage service levels. Also adjusting the cycle times according to power of two policy, it is suggested that orders can be coordinated and capacity usage can be improved. In addition cycle times which ensuring capacity constraint, are obtained with better cost performance. Firstly some information about inventory, which is important for inventory management, are given and the effects of these information to inventory management are explained. Secondly the parameters, which affect the models, are used in inventory management, and general inventory models are examined. After parameter examination the existing capacity constrainted inventory models and the models which can be implemented with random storage and power of two policy are examined. At the application section, the models proposed in this study are applied in a example problem.