An EOQ deteriorating inventory model with different types of demand and fully backlogged shortages
Abu Hashan Md Mashud
International Journal of Logistics Systems and Management, 2020, vol. 36, issue 1, 16-45
Abstract:
The objective of this paper is to develop a deteriorating EOQ inventory model according to consideration of the price, stock dependent demand and fully backlogged shortages. In this model, it is described that the demand functions are: 1) a linear price with stock dependent; 2) price with negative power of constant; 3) exponential function of the price. The deterioration is considered as an instantaneous, i.e., when the item stock in retailer's house after any time deterioration will start. If there any shortages are allowed then it is fully backlogged. The corresponding inventory problem forms a nonlinear constraint optimisation problem. To optimise the problems, the Taylor series expansion is used and considered up to second order term to find the closed form of cycle length and total cost. To validate our result, a comparative approach between our result and some of other meta-heuristics algorithm is given. Also, a sensitivity analysis is being carried out to study the effect of changes of different inventory parameters while changing one parameter at a time and keeping the others value of parameters unchanged.
Keywords: fully backlogged shortages; inventory; deterioration; different price dependent demand. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=107220 (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:36:y:2020:i:1:p:16-45
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 ().