A simulation-optimisation approach for production control strategies in perishable food supply chains
Ahmed Gailan Qasem,
Faisal Aqlan,
Abdulrahman Shamsan and
Mohammed Alhendi
Journal of Simulation, 2023, vol. 17, issue 2, 211-227
Abstract:
In order to minimise wastes and losses in perishable Food Supply Chains (FSCs), it is crucially important to control inventory and organise the flow of material and information throughout supply chains. In this study, Basestock-Constant Work-in-Process (B-CONWIP), a pull-based inventory control policy, is proposed to control inventory in perishable FSCs. The effectiveness of the B-CONWIP policy is investigated for a three-echelon perishable FSC using a simulation-optimisation approach. The B-CONWIP policy is compared with two existing basestock policies (BSPs): continuous review (s, S) policy and BSP-low-Estimated Waste (BSP-low-EW), a periodic inventory review policy that outperforms other policies presented in the literature for perishable inventory. The objective is to minimise the total cost (i.e., sum of holding, deterioration, ordering, and shortage costs) while satisfying a predetermined service level. The study shows that B-CONWIP yields the lowest total cost, BSP-low-EW performs the second best, while (s, S) policy is the worst. It is also noted that, in spite of higher ordering cost for B-CONWIP compared to (s, S) policy and BSP-low-EW, B-CONWIP achieves the lowest total cost at all demand rate and volume variations tested. In conclusion, B-CONWIP is more flexible and robust than (s, S) and BSP-low-EW policies because of its ability to handle demand variations without major changes in control parameter values and cost measures.
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/17477778.2021.1991850 (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:17:y:2023:i:2:p:211-227
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjsm20
DOI: 10.1080/17477778.2021.1991850
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 ().