A Fuzzy-Dominance-Driven MOGA and its application in Nutrition Meal Prescription

In this paper, we study the fuzzification of the pareto dominance relation and its application in Nutrition Meal Prescription. A generic ranking scheme is presented that assigns dominance degrees to any set of vectors in a scale-independent, nonsymmetric and set-dependent manner. Different fuzzy-based definitions of optimality and dominated solution are introduced. The corresponding extension of the Standard Genetic Algorithm, so-called Fuzzy-Dominance-Driven MOGA (FMOGA), will be presented as well. To verify the usefulness of such an approach, the approach is tested on analytical test cases in order to show its validity. The solutions, provided by the proposed algorithm for the Nutrition Prescription Model,are promising when compared with an existing well-known algorithm.