Single-Product Assemble-to-Order Systems with Exogenous Lead Times

Abstract

Efficient Algorithm for Base Stock Policy Optimization in Single-Product Assemble-to-Order Systems with Stochastic Lead Times Single-product assemble-to-order systems can be commonly observed in industrial settings. For example, firms targeting a niche market often choose to offer a single product; moreover, sole-product rollout is usually a preferable business strategy for manufacturers promoting a brand-new product or trying to penetrate a new market. However, maintaining an effective inventory management for those systems is a notoriously difficult problem, especially when the order lead times exhibit stochastic patterns. In “Single-Product Assemble-to-Order Systems with Exogenous Lead Times,” Muharremoglu, Yang, and Geng investigate the case with a special type of stochastic lead time and utilize a certain analysis technique to develop an efficient algorithm for the performance evaluation of base stock policies. In addition, efficiently computable upper and lower bounds are proved based on the key idea of the algorithm. Extensive numerical studies show that the heuristics and the approximation methods developed from those bounds perform well in base stock optimization.