What is it about?

Harvest Hope Food Bank (HHFB), based in South Carolina, serves primarily donated food to people in need in 20 counties across the state. It distributed 28 million pounds of food and fed over two million individuals in fiscal year 2014–2015. However, this constituted only 40 percent of the annual meal gap of about 70 million pounds in its service area. One of HHFB’s major strategic goals is to efficiently utilize its operating budget and its human and technical resources to increase food and dollar donations, which it raises through events corresponding to various promotional initiatives. We worked with HHFB management and staff to develop resource-capacity bills (i.e., the consumption of each resource per event), and calculated the expected food and (or) dollar donation yield per event. We then developed an integer programming optimization model to determine the optimal number of events of each initiative per year with the objective of maximizing the total annual meals yield (i.e., the number of meals that could be served using the food and dollar donations), subject to resource constraints and the allowable number of events of each initiative as advised by HHFB management.

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Why is it important?

With our recommended optimal strategy, HHFB can provide 1.72 million additional meals per year (an increase of 41 percent) from these promotional events within the existing resource limits, which can help bridge the meal gap in its service area. HHFB has embedded the optimization model in its strategic planning of promotional events, and the allocation of resources to support these initiatives, to ensure that it can meet its 5- and 10-year meal-coverage targets. The project framework and model have applicability to food banks and other nonprofit organizations who must raise funds and resources to meet their social service and community-service missions.

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This page is a summary of: Harvest Hope Food Bank Optimizes Its Promotional Strategy to Raise Donations Using Integer Programming, INFORMS Journal on Applied Analytics, August 2018, INFORMS,
DOI: 10.1287/inte.2018.0944.
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