International Journal of Soft Computing And Artificial Intelligence (IJSCAI)
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Volume-7,Issue-2  ( Nov, 2019 )
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  Journal Paper

Paper Title
Application Of Genetic Algorithms For Optimization Of Inventory Using Supply Chain Management

Summary Inventory management plays a vital role in supply chain management. 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. 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. Minimizing the total supply chain cost is meant for minimizing holding and shortage cost in the entire 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. A serious issue in the implementation of the same is that the excess stock level and shortage level is not static for every period. In this paper, we have developed a new and efficient approach that works on Genetic Algorithms and Web Technology in order to distinctively 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. Index Terms— Algorithm, Crossover, Genetic Algorithm, Genetic Operations, Inventory Optimization, Inventory Control, Mutation, Selection, Supply Chain Management.

Author - Vinita Poptani, Shilpa Verma

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| Published on 2016-06-09
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