No 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.