Inventory parameters for a serial supply chain with lost sales through genetic algorithm approach
R. Rajasekaran,
A. Pal Pandi,
P.V. Rajendra Sethupathi and
R. Rajesh
International Journal of Enterprise Network Management, 2018, vol. 9, issue 1, 22-46
Abstract:
Supply chain is a network of facilities with varying conflicting objectives and decision making is a complex process. The uncertainty in demand increases complexity in inventory control mechanism. Backordering, partial backordering and lost-sales are considered in the inventory management to characterise the excess demand. In the present competitive scenario, mostly consumers have no patience to wait and show urgency to buy their goods failing which the management has to meet a huge loss of supply chain members and hence the profit. There are very few research works regarding lost-sales parameter in the area of multi-echelon inventory systems. It is felt that the proposed modified gene-wise genetic algorithm (MGGA) supply chain model which so far not applied in this process may help to determine best base stock levels and review periods with lost sales particularly at retailer end which minimised total supply chain cost.
Keywords: inventory management; genetic algorithm; supply chain model; lost sales. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=92059 (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:ijenma:v:9:y:2018:i:1:p:22-46
Access Statistics for this article
More articles in International Journal of Enterprise Network Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().