ترکیب دو اشتباه برای ایجاد دو حقوق: کاهش خطر ناامنی غذایی و زباله های مواد غذایی از طریق عملیات خالی کردن

Two concurrent social issues in the United States are food insecurity and food waste. The practice of gleaning offers a mechanism for combining these problems to create a synergistic solution. We develop a stochastic optimization model to determine the schedule that maximizes the volume of excess crops rescued from farm fields for the purpose of feeding food-insecure households, thus maximizing social impact. We model gleaning as a service operation where donation calls arrive randomly requesting to be scheduled within a limited time window. The feature that distinguishes gleaning operations from other service settings is that there is uncertainty in both when donations will arrive and the attendance of the gleaners who are volunteers that are not obliged to attend gleaning trips. We apply our model to the gleaning operation of the Food Bank of the Southern Tier in New York State, focusing on five major crops produced in the region. By characterizing how the gleaning operation behaves, our model allows us to optimize the gleaning schedule to maximize the expected total volume gleaned and determine under which conditions different operational strategies can be most useful for improving the performance of the gleaning operation. This in turn enables us to identify conditions under which alternative policy interventions (e.g., farm donation tax credits and government grants to strengthen operational capacity) are more effective for scaling up gleaning programs.