Mathematical Modelling of Diet Planning Problem for Hypertension Patients


  • Nuridawati Baharom Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perlis Branch, Arau Campus
  • Nur Shamien Alfiera Muhamad Isa Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perlis Branch, Arau Campus



linear programming, integer programming, Mathemathical Modelling, Mathematical Model, Hypertension , Diet Planning, High Blood Pressure management


Hypertension or high blood pressure is also called a “silent killer” that may lead to serious damage to the heart and kidney. The worst case can result in sudden death. Unbalanced diets are one of the risk factors for hypertension. Previous studies have proven that diet plays a significant role in influencing hypertension patient condition. Proper planning on the selection of diets needs to be done to control food intake for this cardiovascular disease patient. This study aims to formulate a mathematical model of diet planning for hypertension patients. Specifically, this study attempts to determine the amount of nutrients need by hypertension patients, to find the cost of the food combination, and to identify the best model between linear programming and integer programming. The research model included 10 types of food groups with 200 variables based on Malaysian recipes and developed a mathematical model using two programming techniques; linear programming and integer programming. The finding showed that the solution provided by the entire programming method has met the constraints and requirements of the food group. The results from the integer programming approach would offer optimal and efficient alternatives to diet planning for patients with hypertension. It can serve as a guideline for hypertension patients on type of food to eat and the correct amount of serving to complete their nutritional plan.


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How to Cite

Baharom, N., & Muhamad Isa, N. S. A. (2021). Mathematical Modelling of Diet Planning Problem for Hypertension Patients. Journal of Computing Research and Innovation, 6(4), 1–9.

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