Shipment consolidation under different delivery date options for e-tailing

In this thesis, we consider a shipment consolidation problem for an e-retailer company which has two type of services for its customers: \regular" and \premium". In the regular service, the e-retailer guarantees a delivery time to its customers. However, in the premium service, customers get their items in negligible or zero amount of time, such as same-day delivery, supplied physical inventories located suffciently close. When a shipment decision is made, it serves both customers of the regular service and small inventories for the premium service. In our study, we analyze shipment consolidation operation given these two services for both deterministic and stochastic demand structure. In the deterministic demand problem, our average profit maximizing model decides the optimal service choice; we provide optimality conditions, an algorithm to find optimal solution, structural analyses and numerical results. In the stochastic demand setting, we evaluate the problem for the regular service which has Poisson demand. Then, we expand the problem by including the premium service which has deterministic demand. For this problem, we present an approximate model for a modified version of the policy used for regular-service-only problem and compare the performance of the approximation with a simulation.