Approximation Algorithms for Perishable Inventory Systems

Approximation Algorithms for Perishable Inventory Systems

0.00 Avg rating0 Votes
Article ID: iaor20164678
Volume: 63
Issue: 3
Start Page Number: 585
End Page Number: 601
Publication Date: Jun 2015
Journal: Operations Research
Authors: , , ,
Keywords: simulation, supply & supply chains, demand, combinatorial optimization, stochastic processes
Abstract:

We develop the first approximation algorithms with worst‐case performance guarantees for periodic‐review perishable inventory systems with general product lifetime, for both backlogging and lost‐sales models. The demand process can be nonstationary and correlated over time, capturing such features as demand seasonality and forecast updates. The optimal control policy for such systems is notoriously complicated, thus finding effective heuristic policies is of practical importance. In this paper, we construct a computationally efficient inventory control policy, called the proportional‐balancing policy, for systems with an arbitrarily correlated demand process and show that it has a worst‐case performance guarantee less than 3. In addition, when the demands are independent and stochastically nondecreasing over time, we propose another policy, called the dual‐balancing policy, which admits a worst‐case performance guarantee of 2. We demonstrate through an extensive numerical study that both policies perform consistently close to optimal.

Reviews

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 Your email address will not be published.