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An ensemble forecasting model for predicting contribution of food donors based on supply behavior

  • S.I.: Design and Management of Humanitarian Supply Chains
  • Published:
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Abstract

Food banks are nonprofit hunger relief organizations that collect donations from donors and distribute food to local agencies that serve people in need. Donors consist of local supermarkets, manufacturers, and community organizations. The frequency, quantity, and type of food donated by each donor can vary each month. In this research, we propose a technique to identify the supply behavior of donors and cluster them based on these attributes. We then develop a predictive ensemble model to forecast the contribution of different donor clusters. Our study shows the necessary behavioral attributes to classify donors and the best way to cluster donor data to improve the prediction model.

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Acknowledgements

We want to thank the Food Bank of Central and Eastern North Carolina for sharing data and continuous information for this research. This research is supported by NSF Partnerships for Innovation Project Flexible, Equitable, Efficient, and Effective Distribution (FEEED) (Award No. IIP-1718672).

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  1. Department of Industrial and Systems Engineering, North Carolina Agricultural and Technical State University, Greensboro, NC, USA

    Shubhra Paul & Lauren B. Davis

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Paul, S., Davis, L.B. An ensemble forecasting model for predicting contribution of food donors based on supply behavior. Ann Oper Res 319, 1–29 (2022). https://doi.org/10.1007/s10479-021-04146-5

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