Family Meal Planning under COVID-19 Scarcity Constraints: A Linear Programming Approach

Steven T. Joanis^1,

¹Heider College of Business, Creighton University, Omaha, Nebraska, United States

Cite this paper:
Steven T. Joanis. Family Meal Planning under COVID-19 Scarcity Constraints: A Linear Programming Approach. Journal of Food and Nutrition Research. 2020; 8(9):484-495. doi: 10.12691/jfnr-8-9-5

Abstract

The “Diet Problem” originated in the 1940s when researchers were tasked with determining the lowest-cost subsistence diet for a U.S. soldier. Originally, the task was accomplished through basic heuristics, but later the problem was solved using the simplex algorithm-the basis for modern linear programming. Enhancements to computing technology enabled further constraint consideration, including environmental and palatability constraints. In late 2019, the COVID-19 pandemic began to sweep the planet, resulting in the unavailability of staple food products in the United States, coupled with stay-at-home requirements. This study aimed to add scarcity constraints (food availability and time) to the Diet Problem to demonstrate that, even during a pandemic, healthy eating can be maintained, visits to the supermarket can be limited to reduce exposure, and this can be done relatively inexpensively. A diversified meal plan for a hypothetical family of four was identified at a total monthly cost of $641.51. This study not only demonstrates that healthy eating can be cost-effectively maintained by consumers during a global pandemic but also that shopping trips can be limited to reduce exposure and maintain social distance. Additionally, linear programming-not normally considered by academic researchers-is showcased as a methodology that can be used by other researchers to solve novel problems.

Keywords:
COVID-19 diet problem linear programming pandemic recommended daily allowances scarcity stigler

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