• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2016, Volume: 9, Issue: 45, Pages: 1-8

Original Article

Modeling Vegetable Food Supply Chain by the Prediction of Yield and Demand for a City to Reduce Food Waste


Tons of vegetables go to waste as they are produced in excess than the current demand and go to waste in storage units without any customer to buy them. The objective of the study is to develop a model that helps in effective distribution of vegetable yield demand. Prediction model was developed using regression analysis to find out the future yield so that the farmer can plan the distribution of his produce. Second phase of the study was aimed at reducing transportation using cost integer programming from distributors to retailers while meeting the demand at the same time. The developed model can predict the future yield value which will be closer to the actual yield value. Future demand can also be determined which will be closer to the actual demand. Based on the yield generated and demand comparison, decision can be incorporated in the distribution of vegetables by the farmer to different regions. If the demand is more than yield, tapping of other sources is done. If the demand is lesser, the part of the yield can be sent to other towns and cities where demand has not been met. Food waste problem can be tackled at the source itself by using this model. Wastage can be reduced considerably which is one of the final benefits that will contribute to the societal welfare and development. The integer programming model done for optimizing the cost of distribution provides a feasible solution to the distributors and retailers and satisfying the demand at the same time. Thus, total cost can be minimized without affecting the efficiency of distribution. Distributors and retailers can optimize their distribution effectively while minimizing the transportation cost as much as possible without affecting the demand. 

Keywords: Food Supply Chain, Integer Programming, Linear Regression, Winter’s Demand Forecast Model, Yield Prediction Model  


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