The "Diet Problem" is one of the earliest applications of linear programming. The objective is to minimize the cost of food while complying with daily nutritional intake requirements. George Dantzig first solved the problem as a linear program, based on earlier work by Nobel Laureate George Stigler.
Key features of this model:
- Description: Select foods that satisfy daily nutritional requirements at minimum cost.
- Category: Diet.
- Type: LP.
- Library: OR-Tools.
- Solver: GLOP.
Notes:
- The model has been modified to run as a Jupyter Notebook.
- The data has been extracted into a separate file.
- Output has been formatted to make it easier to read.
GitHub: Diet in OR-Tools.
Key features of this model:
- Description: Select foods that satisfy daily nutritional requirements at minimum cost.
- Category: Diet.
- Type: LP.
- Library: PuLP.
- Solver: CBC.
Notes:
- Reads data from Excel workbook.
GitHub: Diet in PuLP.
Key features of this model:
- Description: Select foods that satisfy daily nutritional requirements at minimum cost. Integer variant, based on the number of servings of each food.
- Category: Diet.
- Type: MILP.
- Library: Pyomo.
- Solver: GLPK.
Notes:
- The model has been modified to run as a Jupyter Notebook.
GitHub: Diet in Pyomo.
Key features of this model:
- Description: Select foods that satisfy daily nutritional requirements at minimum cost.
- Category: Diet.
- Type: LP.
- Library: SciPy.
- Solver: HiGHS.
Notes:
- The data has been extracted into a separate file.
- Method changed from 'simplex' (legacy) to use HiGHS solver.
GitHub: Diet in SciPy.
