skip to main content

Title: Proceedings of the 2018 IISE annual conference
Food insecurity affects more than 41 million people annually in the United States. Within the Feeding America network, approximately 200 food banks are working throughout the US to serve people in need with donated food. Satisfying hunger need of food insecure people with limited supply is a challenge for these food banks. A numerical study is performed on data from Food Bank of Central and Eastern North Carolina (FBCENC) to capture the major attributes controlling its food distribution system. FBCENC seeks to distribute donated food equitably so that each service area (county) receives food proportional to its demand while minimizing the undistributed food donations. In addition to seeking equitable and effective food distribution policies, FBCENC wants to identify distribution branches to maximize the accessibility of the counties to donated food. An assignment and distribution model is developed to minimize the cost of maintaining a user-specified cap on the maximum inequity in food distribution. A sensitivity analysis between the user-specified maximum inequity cap and effectiveness shows the effectiveness of donated food distribution can be improved significantly by sacrificing equitable distribution slightly.
Award ID(s):
Publication Date:
Journal Name:
Modeling for Efficient Assignment of Multiple Distribution Centers for the Equitable and Effective Distribution of Donated Food
Page Range or eLocation-ID:
Sponsoring Org:
National Science Foundation
More Like this
  1. Food banks operate with an objective to serve as many of food-insecure people as possible with the limited supply available to them. This paper presents a mixed-integer programming model to identify the efficient assignment of demand zones (counties) to distribution centers (branches) and equitable allocation of donated food from the food bank branches to the demand zones. The model objective function minimizes the total cost of branch operation, the cost of receiving and distributing food, the cost of undistributed food while maintaining the maximum allowed deviation from perfect equity. Data from the Food Bank of Central and Eastern North Carolina (FBCENC) are used to characterize the major attributes controlling the food distribution system of a food bank. Results from the optimization model using FBCENC data show that the optimal allocation under perfect equity follows a particular structure depending on the shipping cost and the cost of undistributed supply. Sensitivity analyses exploring the trade-offs between efficiency and effectiveness as a function of the cost of shipping, truck capacity, and a user-specified maximum inequity cap show that marginal sacrifice in equity can significantly improve effectiveness. The corresponding improvement in effectiveness is greater when comparatively larger trucks are used and the cost ofmore »shipping is relatively higher. The analyses also suggest that while efficiency is less sensitive to the allowable limit on the deviation from perfect equity, it is sensitive to truck size. A comparison of direct shipping to branches to operating a local hub suggests the former option to be more cost efficient.« less
  2. According to Feeding America, prior to the pandemic, 1 in 5 African-American/Black, 1 in 6 Hispanic, and 1 in 4 Native American households were food insecure compared to 1 in 11 White households. The pandemic is expected to exacerbate these disparities given its disproportionate economic and health impact on historically marginalized racial and ethnic populations. Food banks are non-profit organizations that work to alleviate food insecurity within their service regions by distributing donated food to households in need. Equitable distribution of donated food is an important criteria for food banks. Existing food banking operations literature primarily focus on geographic equity, i.e., where each geographic block of a food bank's service region receives food in proportion to its demand. However, hunger-relief organizations such as food banks are gradually incorporating demography-based equity in their distribution of donated food in light of the disparities that exist within different demographic groups, such as race, age, and religion. However, the notion of demographic equity has not received attention in the food banking operations literature. This study aims to fill in the gap by developing a multi-criteria optimization model to identify optimal distribution policies for a food bank considering a two-dimensional equity criterion, geographic and demographic,more »in the presence of effectiveness (undistributed food minimization) and efficiency (distribution cost minimization) criteria. We apply the model to our partner food bank's data to (i) explore the trade-off between geographic and demographic equity as a function of effectiveness, and efficiency, and (ii) identify policy insights.« less
  3. The United Nations Sustainable Development Goals provide a road map for countries to achieve peace and prosperity. In this study, we address two of these sustainable development goals: achieving food security and reducing inequalities. Food banks are nonprofit organizations that collect and distribute food donations to food-insecure populations in their service regions. Food banks consider three criteria while distributing the donated food: equity, effectiveness, and efficiency. The equity criterion aims to distribute food in proportion to the food-insecure households in a food bank's service area. The effectiveness criterion aims to minimize undistributed food, whereas the efficiency criterion minimizes the total cost of transportation. Models that assume predetermined weights on these criteria may produce inaccurate results as the preference of food banks over these criteria may vary over time, and as a function of supply and demand. In collaboration with our food bank partner in North Carolina, we develop a single-period, weighted multi-criteria optimization model that provides the decision-maker the flexibility to capture their preferences over the three criteria of equity, effectiveness, and efficiency, and explore the resulting trade-offs. We then introduce a novel algorithm that elicits the inherent preference of a food bank by analyzing its actions within a single-period.more »The algorithm does not require direct interaction with the decision-maker. The non-interactive nature of this algorithm is especially significant for humanitarian organizations such as food banks which lack the resources to interact with modelers on a regular basis. We perform extensive numerical experiments to validate the efficiency of our algorithm. We illustrate results using historical data from our food bank partner and discuss managerial insights. We explore the implications of different decision-maker preferences for the criteria on distribution policies.« less
  4. The amount of food waste generated by the U.S. is staggering, both expensive in economic cost and environmental side effects. Surplus food, which could be used to feed people facing food insecurity, is instead discarded and placed in landfills. Institutions, universities, and non-profits have noticed this issue and are beginning to take action to reduce surplus food waste, typically by redirecting it to food banks and other organizations or having students transport or eat the food. These approaches present challenges such as transportation, volunteer availability, and lack of prioritization of those in need. In this paper, we introduce PittGrub, a notification system to intelligently select users to invite to events that have leftover food. PittGrub was invented to help reduce food waste at the University of Pittsburgh. We use reinforcement learning to determine how many notifications to send out and a valuation model to determine whom to prioritize in the notifications. Our goal is to produce a system that prioritizes feeding students in need while simultaneously eliminating food waste and maintaining a fair distribution of notifications. As far as we are aware, PittGrub is unique in its approach to eliminating surplus food waste while striving for social good. We comparemore »our proposed techniques to multiple baselines on simulated datasets to demonstrate effectiveness. Experimental results among various algorithms show promise in eliminating food waste while helping those facing food insecurity and treating users fairly. Our prototype is currently in beta and coming soon to the Apple App Store.« less
  5. 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.