Title

Asymptotic Optimality of (r,Q) Inventory System in a stochastic parallel processing environment

Publication Type

Working Paper

Publication Date

2014

Abstract

We consider a single-item continuous-review (r, q) inventory system with i.i.d. stochastic leadtimes. Using stationary marked point process and a heavy traffic limit, we prove a previous conjecture that inventory position and inventory on-order are asymptotically independent. We also establish closed-form expressions for the optimal policy parameters and system cost in heavy traffic limit, the first of their kind to our knowledge. These expressions sharpen our understanding on the joint effect of lead time variance and lot size. For instance, they demonstrate that the well-known square root relationship between the optimal order quantity and demand rate under a sequential processing environment is replaced by the power of 1/3 under a stochastic parallel processing environment. We further extend the study to periodic-review (S,T) systems with constant leadtimes.

Keywords

inventory system, (r, q) policy, stochastic leadtime, asymptotic analysis, heavy traffic limit.

Discipline

Business

Research Areas

Operations Management

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