With the raise of diseases related with unhealthy lifestyles such as heartattacks, overweight, diabetes, etc., encouraging healthy and balanced patterns in the population is one of the most important action points for governments around the world. Furthermore, it is actually even a more critical situation when a high percentage of patients are children and teenagers whose habits consist merely in eating fast or ultra-processed food and a sedentary life. The development of healthy and balanced menu plans becomes a typical task for physicians and nutritionists, and it is at this point that Computer Science has taken an important role. Discovering new approaches for generating healthy and balanced, as well as inexpensive menu plans will play an important part in banish of diseases from actual and new generations. In this Master Thesis, a recently proposed Evolutionary Algorithm has been compared to other state-of-art evolutionary algorithms for solving the Menu Planning Problem. In order to evaluate the performance of the developed algorithm, an exhaustive experimental assessment was made. Firstly, we focused on evaluating the parameter setting of the algorithm so afterwards the best configuration found could be compared with other well-known algorithms
