A Study Of Supply Chain Management Using Genetic Algorithm In Inventory Optimization For Warehouse

Authors

  • Diwaker Sharma Modern Academy of B.Ed College Ghaziabad (U.P.), India

DOI:

https://doi.org/10.48165/tjmitm.2020.1008

Keywords:

Inventory Optimization, Supply Chain, Warehouse, Artificial bee colony algorithm, Genetic Algorithm

Abstract

In this paper we study a new dimension on warehouse with Artificial bee colony algorithm using genetic algorithm processes in Six Stages - 11 Member Supply Chain in inventory optimization to describe the certain and uncertain market demand which is based on supply reliability and to develop more realistic and more flexible models. The proposed study has a great potential to solve various practical tribulations related to the warehouse using genetic algorithm processes in Six Stages - 11 Member Supply Chain in inventory optimization. It provides a general review for the application of soft computing techniques like genetic algorithms for the improvement of effectiveness and efficiency for various aspect of warehouse with Artificial bee colony algorithm using genetic algorithm.

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Published

2020-12-10

Issue

Vol. 11 No. 1 (2020): Trinity Journal of Management, IT & MEDIA, (Jan-Dec), 2020

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

A Study Of Supply Chain Management Using Genetic Algorithm In Inventory Optimization For Warehouse. (2020). Trinity Journal of Management, IT & Media (TJMITM), 11(1), 48–55. https://doi.org/10.48165/tjmitm.2020.1008
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