A diet expert system utilizing linear programming models in a rule-based inference engine

Abstract

Linear programming is commonly used for solving complex problems in various fields, such as dietetics. Expert systems use expertise and inference procedures to solve problems that require advanced expert knowledge and are also applied to health related problems. Over the years many variations and facets of the diet problem and other related problems have been solved by means of linear programming techniques as well as expert systems. In this research, an expert system was created for the purpose of solving multiple facets of the diet problem, by creating a rule-based inference engine consisting of goal programming- and multi-objective linear programming models. The program was successfully applied to case studies specific to South African teenage girls, which were obtained through the knowledge acquisition phase. The resulting system compiles an eating-plan for a girl that conforms to the nutritional requirements of a healthy diet, includes the personal food preferences of the girl, and consists of food items that result in the lowest total cost. The system also allows prioritization of the food preference and least cost factors by means of weighted priorities.