A production-inventory model in vendor managed inventory system with deteriorating items and pricing in fuzzy environment
Masoud Mohammadzadeh and
Abolfazl Mirzazadeh
International Journal of Logistics Systems and Management, 2018, vol. 29, issue 3, 296-326
Abstract:
In this paper, we develop a vendor managed inventory system for a supply chain with two levels. First level is one manufacturer and second level is several non-competing retailers. The manufacturer produces a deteriorating product from a deteriorating raw material. All deteriorating rates assumed as fuzzy numbers. The demands in retailers are price sensitive based on predefined function with fuzzy parameters. The manufacturer can produce products at a variable production rate that is one of the decision variables of our model. Other decision variables are retail price, the replenishment frequency of raw material, the replenishment cycle of the product that obtained by maximising the total profit of the entire chain. Because of concavity of the profit functions, with a solution algorithm, the exact optimal solution was found. At the end, a numerical example is presented to illustrate the model performance with a sensitivity analysis. Finally, some conclusions and future research directions are proposed.
Keywords: vendor managed inventory; VMI; pricing; production rate; fuzzy deteriorating rate; nonlinear optimisation. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=89789 (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:ids:ijlsma:v:29:y:2018:i:3:p:296-326
Access Statistics for this article
More articles in International Journal of Logistics Systems and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().