Data Science Project: Solving the Diet Problem with Optimization

This project addresses the Diet Problem, a classic optimization challenge in operations research, aiming to find the most cost-effective combination of foods that meet daily nutritional requirements. The solution involves formulating a linear programming model to minimize food costs while adhering to constraints on calories, vitamins, minerals, fats, sodium, and cholesterol. The project requires building Excel spreadsheets to present food data (price, weight, calories, etc.), nutritional requirements, and user consumption data. A user interface, including forms for food selection, data updates, and problem solving, is also essential. The project culminates in a form presenting the solution details (total price, food amounts, nutritional intake) and enabling sensitivity analysis. Furthermore, the project includes designing a logo, creating reports detailing the solution and sensitivity analysis, and plotting daily calorie and monetary expenditures, along with nutritional intake trends. The reference provided is Winston, L.W., “Operations Research: Applications and Algorithms.”