Nutritional Analysis and Optimization of College Students' Dietary Recipes Based on Entropy Weight TOPSIS Method and Simulated Annealing Algorithm

This study aims to optimize the diet of college students through scientific methods to ensure balanced nutrition and maximize economic benefits. The core of the study was the construction of a comprehensive evaluation index system, which covered key nutritional dimensions such as food diversity, energy intake and distribution, macronutrient ratio, and Amino Acid Score (AAS). On this basis, this paper adopts the goal programming method and combines the modern optimization algorithm. Including Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms, the diet recipes are analyzed and designed in depth. In particular, the Entropy Weight Method was introduced to determine the weight of each nutrient evaluation index, which enhanced the objectivity and scientificity of the evaluation system. Then, the improved TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method was used to conduct a comprehensive evaluation of the optimized diet scheme, ensuring the accuracy and reliability of the evaluation results. The dietary plan optimized by the algorithm not only meets the requirements of energy intake and macronutrient ratio, but also realizes effective cost control while ensuring the comprehensiveness of nutrition. The results of the study showed that the optimized dietary regimen for both male and female college students significantly improved their amino acid scores and cost-effectiveness.