Analysis and optimisation of perishable inventory with stocks-sensitive stochastic demand and two-stage pricing: A discrete-event simulation study

Yilin Zhang, Haibing Lu, Zhili Zhou, Zhen Yang and Shengjun Xu

Journal of Simulation, 2021, vol. 15, issue 4, 326-337

Abstract: This paper studies an important real-life perishable inventory management problem, which has not been properly addressed by the existing research. In the problem setting, a number of agents are renting spaces/shelves from a landlord, the inventory capability of each agent is limited to the rent space, and agents are risk-averse due to their budget. The objective is to maximize the profits of the agents/retailers while minimizing waste and improving customers’ shopping experience. To approach the problem, we develop a discrete-event simulation model to determine the optimum inventory scheme for displaying perishables. The proposed simulation model can show sales trajectories with respect to various features and estimate profit curves. Our model improves profits by choosing the right replenishment threshold and price discount. This study has implications to agents/retailers who deal with inventory scheduling and pricing problems for perishables under stochastic conditions.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/17477778.2020.1745703 (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:tjsmxx:v:15:y:2021:i:4:p:326-337

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjsm20

DOI: 10.1080/17477778.2020.1745703

Access Statistics for this article

Journal of Simulation is currently edited by Christine Currie

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