doi: 10.7763/IJMO.2012.V2.203
Genetic Algorithm Based Multi Product and Multi Agent Inventory Optimization in Supply Chain Management
Tarun Kumar
1
,
S. R. Singh
2
,
C. B. Gupta
3
- 1 Computer Science Engg. Dept., Bansthali University Bansthali (Raj.) India
- 2 Mathematics Dept, D. N. College, Meerut (U.P.) India
- 3 Mathematics Dept., BITS, Pilani, Rajasthan, India
Abstract
We propose a technique based on genetic algorithm to optimize inventory in supply chain management .We focus on to specifically determine the most probable excess stock level and shortage level required for inventory optimization in the supply chain such that the total supply chain cost is minimized. The complexity of the problem increases when more products and multiple agents are involved in inventory management process that has been resolved in this work. We apply our method on six member of supply chain studied model for optimization.
Keywords
- Genetic algorithm
- inventory optimization
- supply chain management
- base stock level
- agents
How to Cite
Tarun Kumar, S. R. Singh, and C. B. Gupta, "Genetic Algorithm Based Multi Product and Multi Agent Inventory Optimization in Supply Chain Management," International Journal of Modeling and Optimization, vol. 2, no. 6, pp. 653-657, 2012. https://doi.org/ 10.7763/IJMO.2012.V2.203
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).