Research Article Open Access

Optimizing Inventory Using Genetic Algorithm for Efficient Supply Chain Management

P. Radhakrishnan, W. M. Prasad and M. R. Gopalan


Problem statement: Today, inventory management is considered to be an important field in Supply chain management. Once the efficient and effective management of inventory is carried out throughout the supply chain, service provided to the customer ultimately gets enhanced. Hence, to ensure minimal cost for the supply chain, the determination of the level of inventory to be held at various levels in a supply chain is unavoidable. Minimizing the total supply chain cost refers to the reduction of holding and shortage cost in the entire supply chain. Efficient inventory management is a complex process which entails the management of the inventory in the whole supply chain and getting the final solution as an optimal one. In other words, during the process of supply chain management, the stock level at each member of the supply chain should account to minimum total supply chain cost. The dynamic nature of the excess stock level and shortage level over all the periods is a serious issue when implementation was considered. In addition, consideration of multiple products leads to very complex inventory management process. The complexity of the problem increases when more distribution centers and agents were involved. Approach: In present research, the issues of inventory management had been focused and a novel approach based on genetic algorithm had been proposed in which the most probable excess stock level and shortage level required for inventory optimization in the supply chain is distinctively determined so as to achieve minimum total supply chain cost. Results: The analysis provided us with an inventory level that made a remarkable contribution towards the increase of supply chain cost. We predicted the optimal inventory levels in all the supply chain members with the aid of these levels. Conclusion: We concluded that it is possible to minimize the supply chain cost by maintaining the optimal stock levels that we predicted from the inventory analysis. This will make the inventory management further effective and efficient thereby enhancing the customer servicing levels.

Journal of Computer Science
Volume 5 No. 3, 2009, 233-241


Submitted On: 5 March 2009 Published On: 31 March 2009

How to Cite: Radhakrishnan, P., Prasad, W. M. & Gopalan, M. R. (2009). Optimizing Inventory Using Genetic Algorithm for Efficient Supply Chain Management. Journal of Computer Science, 5(3), 233-241.

  • 5 Citations



  • Supply chain management
  • inventory control
  • inventory optimization
  • genetic algorithm
  • supply chain cost