Understanding the sustainability of retail food recovery
In this paper we study the simultaneous problems of food waste and hunger in the context of food (waste) rescue and redistribution as a means for mitigating hunger. To this end, we develop an empirical model that can be used in Monte Carlo simulations to study the dynamics of the underlying problem. Our model's parameters are derived from a data set provided by a large food bank and food rescue organization in north central Colorado. We find that food supply is a non-parametric heavy-tailed process that is well modeled with an extreme value peaks over threshold model. Although the underlying process is stochastic, the basic approach of food rescue and redistribution to meet hunger demand appears to be feasible. The ultimate sustainability of this model is intimately tied to the rate at which food expires and hence the ability to preserve and quickly transport and redistribute food. The cost of the redistribution is related to the number and density of participating suppliers. The results show that costs can be reduced (and supply increased) simply by recruiting additional donors to participate. With sufficient funding and manpower, a significant amount of food can be rescued from the waste stream and used to feed the hungry.