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.