1 research outputs found
Multi Product Inventory Optimization using Uniform Crossover Genetic Algorithm
Inventory management is considered to be an important field in Supply Chain
Management because the cost of inventories in a supply chain accounts for about
30 percent of the value of the product. The service provided to the customer
eventually gets enhanced once the efficient and effective management of
inventory is carried out all through the supply chain. The precise estimation
of optimal inventory is essential since shortage of inventory yields to lost
sales, while excess of inventory may result in pointless storage costs. Thus
the determination of the inventory to be held at various levels in a supply
chain becomes inevitable so as to ensure minimal cost for the supply chain. The
minimization of the total supply chain cost can only be achieved when
optimization of the base stock level is carried out at each member of the
supply chain. This paper deals with the problem of determination of base stock
levels in a ten member serial supply chain with multiple products produced by
factories using Uniform Crossover Genetic Algorithms. The complexity of the
problem increases when more distribution centers and agents and multiple
products were involved. These considerations leading to very complex inventory
management process has been resolved in this work.Comment: IEEE format, International Journal of Computer Science and
Information Security, IJCSIS January 2010, ISSN 1947 5500,
http://sites.google.com/site/ijcsis