Analysis of Make(Repair)-to-stock Queues with State-dependent Arrival Rates

In this thesis, we study the repair shop scheduling problem(repair-to-stock) and the production/inventory system pricing and production scheduling problem(make-to-stock). For both types of problems, we compare the performance of different scheduling policies. For the make-to-stock type problem, we also study the performance of different pricing strategies. The optimal repair/production scheduling policy of both problems is difficult to characterize, and, therefore, is only formulated as a Markov Decision Process to numerically compute the optimal cost/profit. As an alternative, we propose the dynamic Myopic policy, which is easy to implement. The numerical study we have conducted demonstrates that the performance of Myopic policy is superior compared to the alternative policies and yields costs very close to the optimal for the repair-to-stock type problem. On the other hand, for the make-to-stock type problems, the performance of Myopic policy is not superior compared to the alternative policies when dynamic pricing strategy is implemented.