Demand Forecasting Using Fuzzy Methods Approach in Supply Chain Management

Authors

  • Satyam Chouksey
  • Amit Soni

DOI:

https://doi.org/10.24113/ijoscience.v7i3.435

Keywords:

Supply Chain Management, Forecast, Machine Learning.

Abstract

Modern businesses are confronted with a variety of challenges in a challenging climate. Companies that succeed are more flexible, and they immediately adopt new or revised concepts for corporate governance. As time goes on, they begin to use these techniques in their everyday work. For a company, forecasting is a vital part of its operations. This is regarded as the most basic input in the SCM department and the company. In the context of SCM functions, companies whose chronological development is close to that of the SCM evolution begin to pay attention to the forecast. This research reveals that the firm’s organization can use the barriers and few practical solutions for forecasting. However, retail organizations are continuously looking for a forecasting approach that will allow them to keep their purchasing and sales in balance.

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Author Biographies

Satyam Chouksey

M.Tech. Scholar

Department of Mechanical Engineering

Sagar Institute of Research and Technology (SIRT), Bhopal, India

 

Amit Soni

Professor

Department of Mechanical Engineering

Sagar Institute of Research and Technology (SIRT), Bhopal, India

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Published

03/27/2021

How to Cite

Chouksey, S. ., & Soni, A. . (2021). Demand Forecasting Using Fuzzy Methods Approach in Supply Chain Management. SMART MOVES JOURNAL IJOSCIENCE, 7(3), 62–68. https://doi.org/10.24113/ijoscience.v7i3.435

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Articles