This thesis deals with unknown demand and control parameters in inventory control. Inventory control involves decisions on what to order when and in what quantity. These decisions are based on information about the demand. Models are constructed using complete demand information; these models ensure that a certain service level is achieved. However, in real life the demand information is not known completely. Often, only some historical demand observations are available, and these are used to estimate the information needed in the inventory models. Using these estimates implies that additional uncertainty is introduced in the model and when this extra uncertainty is not taken into account, this could lead to not achieving the desired service level. This thesis shows that this will happen. Furthermore, the size of the underperformance is determined and also methods to reduce it are constructed. However, these methods imply a higher on-hand inventory, which leads to higher inventory costs. So, it might be wiser to address the causes of uncertainty than to treat its symptoms.
|Qualification||Doctor of Philosophy|
|Award date||7 May 2010|
|Place of Publication||Tilburg|
|Publication status||Published - 2010|