Optimal Production Control under Uncertainty with Revenue Management Considerations.

Abstract

This dissertation consists of three essays on supply chain and revenue management. Its main focus is the integration of dynamic production and demand management decisions for multiple products facing uncertain demand. The study considers three problem settings to inquire into flexibility's influence on a dynamic pricing strategy, managing exogenous demand for intermediary products, and allocation of shared resources among multiple products in a make-to-order environment.

The first chapter studies a joint mechanism of dynamic pricing and capacity flexibility to mitigate demand and supply mismatches. We consider a firm producing two substitutable products with price-correlated demands utilizing capacitated product-dedicated and flexible resources. We characterize the structure and sensitivity of the optimal production and pricing decisions and find that the existence of a flexible resource in the firm's capacity portfolio helps maintain stable price differences across items over time. This result has favorable ramifications from a marketing standpoint as it suggests that even when a firm applies a dynamic pricing strategy, it may still establish consistent price positioning among multiple products if it can employ a flexible replenishment resource. We also investigate the economic benefits of a joint strategy versus applying each tool individually.

The second chapter considers a setting where several intermediate products are assembled into an end product with external demand for both the end and intermediary products. We address the questions on how to decide on the production quantities for each component, when to initiate an assembly operation and how to set admission rules for demands targeted at various products. We characterize the structure and sensitivity of the optimal policy and extend the model to multiple customer classes and partial revenue collecting schemes. We propose a novel heuristic policy that is efficient, easily implementable and robust with respect to the number of intermediate products.

Finally, the third chapter studies a basic mass customization setting by focusing on a manufacturing firm that assembles products to customer orders. For a two-stage production-assembly operation, we partially characterize the optimal production and demand admission control decisions. Based on the insights gained, we propose a heuristic algorithm and provide computational results on its performance.