A stochastic program based lower bound for assemble‐to‐order inventory systems

A stochastic program based lower bound for assemble‐to‐order inventory systems

0.00 Avg rating0 Votes
Article ID: iaor20121921
Volume: 40
Issue: 2
Start Page Number: 89
End Page Number: 95
Publication Date: Mar 2012
Journal: Operations Research Letters
Authors: ,
Keywords: combinatorial optimization, programming: probabilistic
Abstract:

In this paper we introduce a multi‐stage stochastic program that provides a lower bound on the long‐run average inventory cost of a general class of assemble‐to‐order (ATO) inventory systems. The stochastic program also motivates a replenishment policy for these systems. Our lower bound generalizes a previous result of Dogru et al. (2010) for systems with identical component replenishment lead times to those with general deterministic lead times. We provide a set of sufficient conditions under which our replenishment policy, coupled with an allocation policy, attains the lower bound (and is hence optimal). We show that these sufficient conditions hold for two examples, a single product system and a special case of the generalized W model.

Reviews

Required fields are marked *. Your email address will not be published.