Abstract:
The main purpose of this thesis is to provide a wholistic model for both pricing and order fulfillment problems of an online retailer. Real sales and shipment data of a company are used for both forecasting and fulfillment decisions. A tree-based en semble model is offered for the demand forecasting process by considering pricing and promotion effects. The generated sales forecasts are added to the fulfillment model as future orders. These orders can be fulfilled by any FCs by considering the corre sponding fulfillment costs. Therefore, the offered data driven model tries to optimize total profit of the company while minimizing these operational costs. These results are compared across different cases for price and capacity levels. Due to the randomness of the generated demand forecasts, a prescriptiveness coefficient is used to evaluate the reliability of the offered results. As a result of this study, an optimal inventory allocation, fulfillment and pricing strategy are provided to the company.
