STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Software Engineering Tools & Technology Trends Review Article

Demand Forecasting for Perishable Food Commodities Using Data Analytics

  1. Advaita Menon School of Technology, Management & Engineering, NMIMS University, Navi Mumbai
  2. Midhir Nambiar School of Technology, Management & Engineering, NMIMS University, Navi Mumbai
  3. Aman Mishra School of Technology, Management & Engineering, NMIMS University, Navi Mumbai
  4. Aryan Tiwari School of Technology, Management & Engineering, NMIMS University, Navi Mumbai
  5. Aditya Kasar School of Technology, Management & Engineering, NMIMS University, Navi Mumbai

Abstract

This paper introduces a comprehensive study aimed at enhancing the forecasting of perishable food item demand. Focusing on solving the critical issue of waste management within the supply chain of food products, the research undertakes a comparative analysis of various machine learning models. The development of an optimized model that is capable of accurately forecasting the demand for perishable food items is the focus of this research. The research includes a review of the literature on demand, pricing, and production prediction studies carried out in India. It argues that machine learning algorithms can generate accurate forecasts and emphasizes the need for improved supply chain management to reduce waste in the perishable foods business. By underlining the need for modeling techniques in the optimization of supply chains for perishable items, this work increases the understanding of demand forecasting. Each entity involved in the supply chain can reduce waste and maximize inventory management with the help of the paper's insightful recommendations and proposed mechanism, thereby benefiting through a reduction in the cost of maintenance of the perishable food products.

Keywords

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