In this thesis, a stochastic (s-1,s) inventory model with finite customers and varying instantaneous demand rate, is studied to find the optimal stock level which minimizes the inventory management cost.
In the operation and maintenance of fleet of equipments which can be modeled as a closed queueing network, it may be also preferable to use one-for-one ordering (s-1, s) policy for the low demand or high cost spare parts. However the finiteness of the fleet size makes the instantaneous demand rate to vary with the state of inventory system. The basic (s-1, s) inventory model is derived from the infinite fleet size, so that the instantaneous demand rate is assumed to be constant. The basic (s-1, s) inventory model cannot be applied to finite fleet case.
In this thesis heuristic method is presented to obtain the optimal stock level for the finite fleet size case. The optimal stock level can be obtained using the basic (s-1, s) inventory model by computing the open queueing network equivalent part demand rate. The validation of this algorithm was done with GPSS simulation and FORTRAN. A computer program based on the heuristic algorithm is included.
