Abstract

This paper presents an approach to optimize the reorder level (ROL) in the manufacturing unit taking consideration of the stock levels at the factory and the distribution centers of the supply chain, which in turn helps the production unit to optimize the production level and minimizing the inventory holding cost. Genetic algorithm is used for the optimization in a multi product, multi level supply chain in a web enabled environment. This prediction of optimal ROL enables the manufacturing unit to overcome the excess/ shortage of stock levels in the upcoming period.

References

• Beamon, B.M., “Supply Chain design and Analysis: Models and Methods”, International Journal of Production Economics, Vol. 55, pp: 281-294, 1998.
• Chandra K. Jaggi, Aggarwal. K.K and Priyanka Verma, “Two Warehouse Inventory Model For Deteriorating Items When Demand Is Price Sensitive”, International Journal of Operational Research, Vol. 7,No. 4, Pg 530 – 543, 2010.
• Gunasekaran. A, Patel. C, Ronald E. McGaughey, “A Framework For Supply Chain Performance Measurement”, International Journal of Production Economics, Vol. 87, pp: 333 – 347, 2004.
• Jeffery Joines, Gupta, Mahmut Ali Gokee, Michael G. Kay, Russell E. King, “Supply Chain Multi Objective Optimization”, Proceeding of the 2002 Winter Simulation Conference, 2002.
• Jianhui Wang, Lin Xu, Shufang Sun and Yongliang Yan, “Optimization of Spare Parts Stores Based on an Improved Genetic Algorithm in a Supply Chain”, International Journal of Information and System Sciences, Vol. 2, No. 1, pp: 59 – 66, 2006.
• Kannan. G, Noorul Haq and Devika . M, “Analysis of Closed Loop Supply Chain using Genetic Algorithm and Particle Swarm Optimization”, International Journal of Production Reearch, Vol. 47, pp 1175 – 1200, 2009.
• Maiti. M and Maity. K, “Optimal Inventory Policies For Deteriorating Complementary And Substitute Items”, International Journal of System Science, Vol. 40, pp:. 267 – 276, 2009.
• Narmadha. S, Selladurai. V, Sathish. G, “Multiproduct Inventory Optimization using Uniform Cross Over Genetic algorithm”, IJCSIS, Vol. 7, No. 1, 2010.
• Narmadha. S, Selladurai. V, Sathish. G, “Efficient Inventory Optimization of multiproduct, multiple suppliers with lead time using PSO”, IJCSIS, Vol. 7, No. 1, 2010.
• Radhakrishnan. P, Prasad V.M. and Jeyanthi. N, “Predictive analysis using Genetic Algorithm for Efficient Supply Chain Management”, Journal of Computer Science and Network Security”, Vol. 10, No. 3, pp:. 1820-0186., 2010.
• Radhakrishnan. P, Prasad. V.M and Jeyanthi. N, “Design of Genetic Algorithm based Supply chain Inventory Optimization with Lead Time”, Journal of Computer Science and Network Security”, Vol. 10, No. 3, pp: 1820-1826, 2010.
• Sean X. Zhou and Xiuli Chao, “Optimal Policy for a Multi Echelon Inventory system with Batch Ordering and Fixed Replenishment Intervals” , Operations Research, Vol. 57, pp: 377-390, 2009.
• Uthayakumar. R and Geetha. K.V, “Replenishment Policy For Single Item Inventory Model With Money Inflation”, Opsearch, Vol. 46, pp: 345-357, 2008.