@article{jfnr2020895,
author={Joanis, Steven T.},
title={Family Meal Planning under COVID-19 Scarcity Constraints: A Linear Programming Approach},
journal={Journal of Food and Nutrition Research},
volume={8},
number={9},
pages={484--495},
year={2020},
url={http://pubs.sciepub.com/jfnr/8/9/5},
issn={2333-1240},
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.<i> </i>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.<i> </i>A diversified meal plan for a hypothetical family of four was identified at a total monthly cost of $641.51<i>.</i> 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.},
doi={10.12691/jfnr-8-9-5}
publisher={Science and Education Publishing}
}