Analysis of Inventory Level Optimization Using PSONN Model and Fuzzy Logic Approach

  • Yogesh . M.Tech. Scholar, Department of M.E, Sagar Institute of Research and Technology Excellence, Bhopal, India
  • Sudhir Shrivastava Assistant Professor & Dean, Department of M.E, Sagar Institute of Research and Technology Excellence, Bhopal, India
Keywords: Raw materials, Inventories, Inventory Management, Artificial Intelligence, Fuzzy rules.

Abstract

Raw materials, intermediate goods and finished goods are termed as inventories while considering it as portion of business’s assets which can be considered as prepared or are prepared for sale. One of the suitable solutions is to design optimal inventory model. Major concern of industry is to design suitable inventory model. Some of the existing inventory management research work are discussed in literature. But this field is still a big area of interest. Many research works used artificial intelligence models for inventory management. One amongst the area for inventory management is worker behavior in a company. So, employees are taken into account to be as an inventory that contributes in growth of an organization. Employee attrition may be a big issue for the organizations specially once trained, technical and key staff leave for a far better chance from the organization. This results in financial loss to replace a trained employee. Therefore, this paper uses the current and past employees’ data to analyze attrition behavior of employees and to provide bonus/promotion to employees having non attrition behavior by using PSONN and fuzzy rules. The result shows that the efficiency of model is improved with respect to existing methods by approximately 2%.

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References

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Published
October 2019
How to Cite
., Y., & Shrivastava, S. (2019). Analysis of Inventory Level Optimization Using PSONN Model and Fuzzy Logic Approach. SMART MOVES JOURNAL IJOSCIENCE, 5(10), 1-6. https://doi.org/10.24113/ijoscience.v5i10.227