An EOQ model for perishable item with stock and price dependent demand rate
Sudhansu Khanra,
Shib Sankar Sana and
Kripasindhu Chaudhuri
International Journal of Mathematics in Operational Research, 2010, vol. 2, issue 3, 320-335
Abstract:
This paper deals with a single-item economic order quantity model where the vendor is in a position to influence demand of customers by its stock display and pricing decision. In general, most of the merchandise have a certain life time after which deterioration starts. In this situation, a good management decides to boost the sales of their products at reduced price to avoid more losses due to deterioration. Consequently, the demand of deteriorating items is an increasing function of reduction rate on selling price. It is thus confronted with simultaneous reduction on selling price and replenishment quantity decisions, which would jointly maximise the expected average profit over an infinite planning horizon. Computational aspects of the proposed model are discussed, and formulation is shown to give successful results on test problems. The sensitivity of the optimal solution to changes in the values of different parameters is also examined.
Keywords: inventory management; stock dependent demand; reduction rate; item deterioration; EOQ modelling; perishable items; price dependent demand; economic order quantity; selling price; replenishment quantity. (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.inderscience.com/link.php?id=32721 (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:ijmore:v:2:y:2010:i:3:p:320-335
Access Statistics for this article
More articles in International Journal of Mathematics in Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().