Healthy nutrition is essential for maintaining health and preventing chronic diseases. However, with the increase in dining out, the prevalence of obesity and related chronic diseases is increasing daily. Therefore, to provide adequate and balanced nutrition in public, it is necessary to serve healthy menus following the energy and nutrient requirements of the target group in food service institutions. However, menu planning in food services is a complex process involving several factors. The planned menus should provide sufficient nutrients for the target group and consider factors such as color, consistency, appearance, and a variety of food groups. In addition, existing studies have limited constraints, and the fact that they are not open -source makes it difficult to conduct more comprehensive new studies. Furthermore, the lack of dietitian opinions limits its applicability in practice. Therefore, this study applied four different multi -objective optimization algorithms (AGEMOEA, SMSEMOA, NSGA2, and NSGA3) to solve the menu planning problems. The results were shared with 20 food service dietitians who are experts in the area and were asked to score the menus. In addition, an open -source tool called EvoMeal has been developed. In conclusion, our primary findings showed that AGEMOEA and SMSEMOA were used for the first time in the literature for the menu planning problem, which is a multi -objective problem, and they performed better than both NSGA2 and NSGA3 in general. In addition, expert opinions confirmed that AGEMOEA and SMSEMOA give better results than other algorithms. However, future studies need to conduct a more comprehensive expert evaluation to increase its applicability to the field.