Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/29261
Title: On the stochastic inventory problem under order capacity constraints
Authors: Rossi, R
Chen, Z
Tarim, SA
Keywords: inventory;stochastic lot sizing;order capacity;modified multi-(s, S) policy
Issue Date: 5-Jul-2023
Publisher: Elsevier
Citation: Rossi, R., Chen, Z. and Tarim, S.A. (2023) 'On the stochastic inventory problem under order capacity constraints', European Journal of Operational Research, 312 (2), pp. 541 - 555. doi: 10.1016/j.ejor.2023.06.045.
Abstract: We consider the single-item single-stocking location stochastic inventory system under a fixed ordering cost component. A long-standing problem is that of determining the structure of the optimal control policy when this system is subject to order quantity capacity constraints; to date, only partial characterisations of the optimal policy have been discussed. An open question is whether a policy with a single continuous interval over which ordering is prescribed is optimal for this problem. Under the so-called “continuous order property” conjecture, we show that the optimal policy takes the modified multi- form. Moreover, we provide a numerical counterexample in which the continuous order property is violated, and hence show that a modified multi- policy is not optimal in general. However, in an extensive computational study, we show that instances violating the continuous order property do not surface, and that the plans generated by a modified multi- policy can therefore be considered, from a practical standpoint, near-optimal. Finally, we show that a modified policy also performs well in this empirical setting.
URI: https://bura.brunel.ac.uk/handle/2438/29261
DOI: https://doi.org/10.1016/j.ejor.2023.06.045
ISSN: 0377-2217
Other Identifiers: ORCiD: Roberto Rossi https://orcid.org/0000-0001-7247-1010
ORCiD: Zhen Chen https://orcid.org/0000-0002-1619-3017
ORCiD: S. Armagan Tarim https://orcid.org/0000-0001-5601-3968
Appears in Collections:Brunel Business School Research Papers

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