ON ASSEMBLE-TO-ORDER SYSTEMS

Abstract

Since the 1990s, facing increasing competition and mass customization, many companies including Dell have chosen to adopt the assemble-to-order (ATO) model in order to increase products offering and reduce the life cycles of products. Inventory management is a key challenge for ATO systems, in particular determination of inventory replenishment levels without full demand information, component allocations based on available component inventories, and realizations of product demands. ATO systems are usually modeled as a two-stage stochastic integer program. However, such programs are typically hard to solve, especially for stochastic integer nonlinear programs used for the joint optimization. In this thesis, we describe two ATO models proposed by Ackay and Xu (2004) and by Huang (2014). Both models include a nonlinear term in the right hand side of the inventory availability constraints. We discuss the techniques used to linearize the original problem and to estimate the impact of the linearization. In addition, we investigate another key element of ATO systems called component commonality used to reduce inventory costs. An extensive literature review regarding component commonality is provided.