Celiac disease multi-purpose diet plan through integrated goal programming and Interval Type 2 Fuzzy TOPSIS method

YILMAZ İ., Polat L.

Expert Systems with Applications, vol.218, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 218
  • Publication Date: 2023
  • Doi Number: 10.1016/j.eswa.2023.119618
  • Journal Name: Expert Systems with Applications
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, Public Affairs Index, Civil Engineering Abstracts
  • Keywords: Celiac Disease, Diet Formulation, Fuzzy Logic, Goal Programming, TOPSIS
  • Ankara Yıldırım Beyazıt University Affiliated: Yes


© 2023 Elsevier LtdSome people are genetically predisposed to Celiac disease, but the process of calling this disease is driven by the ingestion of gluten. This disease affects the person's immune system. Therefore, people must follow a gluten-free diet to prevent the progression of their disease and improve their quality of life. This research aims to raise awareness for celiac patients by providing a novel decision-support model and improving the daily nutritional diets of these patients in line with the determined objectives. A sample gluten-free diet is modeled for low-activity women aged 19–30. In the proposed diet sample, the composition of nutrients and objectives are provided by a dietician. The objective of this study is to minimize these target values in this diet. Celiac disease patients need to meet as much as possible predefined 8 objectives when the patients follow their diet. The Goal Programming (GP) methodology is applied to reach minimum deviations from these 8 objectives. Before GP, a Multi-Criteria Decision Making (MCDM) process is applied to rank and get the weights of objectives. For this process, the Interval Type 2 Fuzzy TOPSIS (IT2FT) method is preferred as an MCDM method. Criteria for IT2FT are determined by examining academic literature and by interviewing relevant dietitians. These criteria are defined as salary, gender, body weight, body length, age, and mobility level. Then, the diet model is created with the information obtained through IT2FT and GP. In the created model, the objectives are determined as constraints. Positive deviations or negative deviations according to the direction of each constraint are included in the calculation together with their weights. In this way, the patient will be fed with the lowest calories and cost, while at the same time she will act following her diet. In conclusion, the values of objectives are minimized.