Shipment Consolidation Under Different Delivery Date Options For E-tailing
M.S. Thesis Presentation by
Department of Industrial Engineering
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 ``extended''. In the regular service, the e-retailer guarantees a delivery time to its customers. However, in the extended service, customers get their items in negligible or zero amount of time, such as same-day delivery, supplied physical inventories located sufficiently close. When a shipment decision is made, it serves both customers of the regular service and small inventories for the extended 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 and we provide optimality conditions, an algorithm to find optimal solution, numerical and structural analyses. In the stochastic demand setting, we evaluate the problem firstly for the regular service which has Poisson demand. Then, we expand the problem by including the extended service which has deterministic demand. For this problem, we present a modified policy for the shipment operation, and compare the performance of our policy with simulation to provide an insight.