Commitment under uncertainty: production-inventory policies associated with environmental considerations

Konstantin Kogan, Dmitry Tsadikovich, Matan Shnaiderman and Beatrice Venturi

Journal of the Operational Research Society, 2024, vol. 75, issue 12, 2312-2326

Abstract: We consider a manufacturer that produces in response to a stochastic demand and emits pollution during the production process. Industrial pollutants released into the air are characterised by spatial variability and heterogeneity, and the precision of instruments for measuring stochastic pollution stocks varies widely across pollutants. Consequently, commitment (open-loop) strategies to control production and associated emissions are considered more practical than contingent (feedback) approaches when manufacturers are concerned about environmental consequences. In this article, we derive an optimal, open-loop control policy over an infinite time horizon and show a condition that ensures that such a policy induces asymptotic convergence of expected inventory stock and pollution stock trajectories to unique steady states. Moreover, we find that the variance in the pollution stock also converges asymptotically to a unique steady state, which is critical for prevention of irreversible environmental consequences. We show that environmental uncertainty affects inventories, leading, in the long run, to lower expected steady-state inventory stocks. We compare feedback and open-loop production policies and show that though there are losses associated with the inability to track inventory and pollution stocks accurately and thus applying the open-loop control instead of feedback, the expected long-term inventory and pollution stocks are not affected.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/01605682.2024.2311877 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjorxx:v:75:y:2024:i:12:p:2312-2326

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjor20

DOI: 10.1080/01605682.2024.2311877

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald

More articles in Journal of the Operational Research Society from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().