Title :
Determining Robust Solutions in Supply Chain Using Genetic Algorithm
Author :
Joseph, Niju P. ; Radhamani, G.
Author_Institution :
Center for R&D, Bharathiar Univ., Coimbatore, India
Abstract :
In the management of Inventory in a supply chain, stock management plays a very important role. The stock level plays a crucial role in any supply chain management. There is a element of uncertainty in the process. The Uncertainty can affect the performance level of the business. The under or over stocking of inventory adversely affects a business. In this paper a genetic algorithm is proposed which tries to find out the optimal holding of stock. This algorithm uses a multiple set of crossover operators and mutation operators for solving the problem. In this paper we try to iterate input uncertain data and compute robust solutions for inventory management in a supply chain.
Keywords :
genetic algorithms; inventory management; supply chain management; crossover operators; genetic algorithm; input uncertain data; inventory management; mutation operators; problem solving; robust solutions; stock management; supply chain; Biological cells; Conference management; Fuzzy systems; Genetic algorithms; Genetic mutations; Inventory management; Robustness; Supply chain management; Supply chains; Uncertainty; Genetic algorithms; Multiple Operators; Repeat Crossover; Uncertain data; learning;
Conference_Titel :
Data Storage and Data Engineering (DSDE), 2010 International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4244-5678-9
DOI :
10.1109/DSDE.2010.35