This paper provides guidance for operating an assemble-to-order system to maximize expected discounted profit, assuming that a high volume of prospective customers arrive per unit time. The first step is to optimize the price and leadtime quoted for each product, and the investment in production capacity for each component. Then the assemble-to-order system dynamics can be approximated by a Brownian motion with dimension equal to the number of components (rather than the number of components plus the number of products). This state-space-collapse facilitates integrated optimal control of component production and inventory. We show how to numerically solve the approximating Brownian control problem and translate the solution into a near-optimal policy for dynamically managing component production and inventory, and sequencing customer orders for assembly. When components can be expedited at large cost but not salvaged, we prove our proposed policy is asymptotically optimal in high volu...
Erica L. Plambeck, Amy R. Ward