English

Efficient Inventory Optimization of Multi Product, Multiple Suppliers with Lead Time using PSO

Neural and Evolutionary Computing 2010-02-11 v1

Abstract

With information revolution, increased globalization and competition, supply chain has become longer and more complicated than ever before. These developments bring supply chain management to the forefront of the managements attention. Inventories are very important in a supply chain. The total investment in inventories is enormous, and the management of inventory is crucial to avoid shortages or delivery delays for the customers and serious drain on a companys financial resources. The supply chain cost increases because of the influence of lead times for supplying the stocks as well as the raw materials. Practically, the lead times will not be same through out all the periods. Maintaining abundant stocks in order to avoid the impact of high lead time increases the holding cost. Similarly, maintaining fewer stocks because of ballpark lead time may lead to shortage of stocks. This also happens in the case of lead time involved in supplying raw materials. A better optimization methodology that utilizes the Particle Swarm Optimization algorithm, one of the best optimization algorithms, is proposed to overcome the impasse in maintaining the optimal stock levels in each member of the supply chain. Taking into account the stock levels thus obtained from the proposed methodology, an appropriate stock levels to be maintained in the approaching periods that will minimize the supply chain inventory cost can be arrived at.

Keywords

Cite

@article{arxiv.1002.2196,
  title  = {Efficient Inventory Optimization of Multi Product, Multiple Suppliers with Lead Time using PSO},
  author = {S. Narmadha and Dr. V. Selladurai and G. Sathish},
  journal= {arXiv preprint arXiv:1002.2196},
  year   = {2010}
}

Comments

IEEE format, International Journal of Computer Science and Information Security, IJCSIS January 2010, ISSN 1947 5500, http://sites.google.com/site/ijcsis/

R2 v1 2026-06-21T14:45:44.642Z