NEAR-OPTIMAL MODIFIED BASE STOCK POLICIES FOR THE CAPACITATED INVENTORY PROBLEM WITH STOCHASTIC DEMAND AND FIXED COST

Okan Örsan Özener (), Refik Güllü () and Nesim Erkip ()
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Okan Örsan Özener: Ozyegin University, Istanbul, Turkey
Refik Güllü: Bogazici University, Istanbul, Turkey
Nesim Erkip: Bilkent University, Ankara, Turkey

Asia-Pacific Journal of Operational Research (APJOR), 2014, vol. 31, issue 03, 1-27

Abstract: In this study, we investigate a single-item, periodic-review inventory problem where the production capacity is limited and unmet demand is backordered. We assume that customer demand in each period is a stationary, discrete random variable. Linear holding and backorder cost are charged per unit at the end of a period. In addition to the variable cost charged per unit ordered, a positive fixed ordering cost is incurred with each order given. The optimization criterion is the minimization of the expected cost per period over a planning horizon. We investigate the infinite horizon problem by modeling the problem as a discrete-time Markov chain. We propose a heuristic for the problem based on a particular solution of this stationary model, and conduct a computational study on a set of instances, providing insight on the performance of the heuristic.

Keywords: Inventory; stochastic processes; capacity restriction; fixed ordering cost (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0217595914500195

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