Optimized Warehouse Management of Perishable Goods

Author:

Kumar M.N. Vimal,Snehalatha S.,Nageswari C. Shobana,Raveena C.,Rajan S.

Abstract

In recent years, food wastage becomes the major problem of the world and researchers indicate that 20-60% of the total production is lost in the food supply chain.[1] Due to perishable nature and the cost of the products fresh food companies face more challenges throughout the supply chains. An order proposal is generated for all the products for a time period of a week by the integration of Machine Learning and loud and also taking into supply chain with some barriers such as supplier delivery times and also the maximum and minimum number of orders. The whole process of prediction is done using Random Forest Regression algorithm. This paper focuses particularly on perishable goods and analyzed based on the accuracy of the training and testing data.

Publisher

Centivens Institute of Innovative Research

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. AI in Managing Perishable Goods Inventory;Advances in Business Strategy and Competitive Advantage;2024-08-30

2. Designing an Energy-Efficient Transportation Network to Transport Perishable Crops: An Aggregated VRP and X-means Clustering Approach;Heliyon;2023-09

3. Machine Learning Enabled Traffic Sign Detection System;2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT);2023-02-22

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