The robust optimization model for providing Iranian diet for adjusting optimal glycemic load

Hoseinpour, Masomeh; Fakharzadeh Jahromi, Alireza

doi:10.22105/dmor.2019.86128

Document Type : original-application paper

Authors

¹ Payam Noor University, Shiraz, Iran.

² Department of Mathematics, Shiraz University of Technology, Shiraz, Iran.

https://doi.org/10.22105/dmor.2019.86128

Abstract

In recent decades, the theory of robust optimization has been introduced as a powerful tool for optimizing uncertain processes. Regarding the Uncertainty of the glycemic load of consumed food, the main purpose of this article is to provide an optimal Iranian diet using a robust optimization to adjust the glycemic load in patients with type 2 diabetes. Diabetes type 2 is a devastating disease, in addition to cardiovascular disease, infectious and kidney diseases, causes insulin resistance and cancer and drugs of cholesterol-lowering have an increased risk of cardiovascular complications and incidence of cancer. Indeed, adjustment of nutrition is important to prevent and control or reduce the complications of diabetes. In this paper, due to the uncertainty of the glycemic load of foods, with collecting necessary nutritional information, the Iranian diet model is determined and analyzed by a robust optimization method. According to this, 75 cases of food (42 Iranian food, 10 Foodstuffs for breakfast, 20 types of fruits and fruit juices and 3 types of dairy products) have been studied locally. The benefits of this model are the ability to adapt according to the person's tastes and opinion of the nutritionist with minimizing changes for the current diet of the individual.

Keywords

Main Subjects

Robust optimization

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Journal of Decisions and Operations Research

The robust optimization model for providing Iranian diet for adjusting optimal glycemic load

References

References

Volume 4, Issue 1
June 2019
Pages 42-53

The robust optimization model for providing Iranian diet for adjusting optimal glycemic load

References

References

Volume 4, Issue 1June 2019Pages 42-53

Volume 4, Issue 1
June 2019
Pages 42-53