DocumentCode
3073353
Title
Genetic Algorithm Based Inventory Optimization Analysis in Supply Chain Management
Author
Radhakrishnan, Pooja ; Prasad, V.M. ; Gopalan, M.R.
Author_Institution
CSE Dept., PSG Inst. of Adv. studies, Coimbatore
fYear
2009
fDate
6-7 March 2009
Firstpage
418
Lastpage
422
Abstract
Inventory management is one of the significant fields in supply chain management. Efficient and effective management of inventory throughout the supply chain significantly improves the ultimate service provided to the customer. Hence there is a necessity of determining the inventory to be held at different stages in a supply chain so that the total supply chain cost is minimized. Minimizing the total supply chain cost is meant for minimizing holding and shortage cost in the entire supply chain. This inspiration of minimizing Total Supply Chain Cost could be done only by optimizing the base stock level at each member of the supply chain. The dilemma occurring here is that the excess stock level and shortage level is very dynamic for every period. In this paper, we have developed a novel and efficient approach using Genetic Algorithm which clearly determines the most possible excess stock level and shortage level that is needed for inventory optimization in the supply chain so as to minimize the total supply chain cost.
Keywords
genetic algorithms; inventory management; supply chain management; genetic algorithm; inventory optimization; shortage level; stock level; supply chain management; Algorithm design and analysis; Costs; Customer service; Genetic algorithms; Inventory management; Manufacturing; Production; Raw materials; Supply chain management; Supply chains; Genetic Algorithm; Inventory Optimization; Inventory control; Supply Chain Management; supply chain cost;
fLanguage
English
Publisher
ieee
Conference_Titel
Advance Computing Conference, 2009. IACC 2009. IEEE International
Conference_Location
Patiala
Print_ISBN
978-1-4244-2927-1
Electronic_ISBN
978-1-4244-2928-8
Type
conf
DOI
10.1109/IADCC.2009.4809047
Filename
4809047
Link To Document