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GLOP - Stigler diet

Problem: choose the cheapest mix of foods that satisfies daily minimum nutrition requirements.

Show code

import { MPSolver } from 'or-tools-wasm/mp-solver';
const solver = MPSolver.createSolver('GLOP');
solver.setNumThreads(4);

const nutrients = [
  { name: 'Calories (kcal)', minimum: 3 },
  { name: 'Protein (g)', minimum: 70 },
  { name: 'Calcium (g)', minimum: 0.8 },
];
const data = [
  { name: 'Wheat Flour', nutrients: [44.7, 1411, 2] },
  { name: 'Macaroni', nutrients: [11.6, 418, 0.7] },
  { name: 'Milk', nutrients: [6.1, 310, 10.5] },
  { name: 'Eggs', nutrients: [2.9, 238, 1] },
  { name: 'Spinach', nutrients: [1.1, 106, 0] },
];

const foods = data.map((food) => solver.addNumVariable(0, solver.infinity(), food.name));

nutrients.forEach((nutrient, nutrientIndex) => {
  const ct = solver.addConstraint(nutrient.minimum, solver.infinity());
  data.forEach((food, foodIndex) => {
    ct.setCoefficient(foods[foodIndex], food.nutrients[nutrientIndex]);
  });
});

const objective = solver.objective();
foods.forEach((food) => objective.setCoefficient(food, 1));
objective.setMinimization();
await solver.solve({ executor: 'worker' });

This is a continuous linear program: foods can be bought in fractional daily units.
The objective is to minimize annual food cost.
Each nutrient is a lower-bound constraint that the selected food mix must satisfy.
Expand any food card to edit its label, unit, color, and nutrient contributions.
Change the nutrient requirement inputs to make the diet easier, harder, or impossible.
The result is a mathematically cheap diet, not a realistic meal plan.

Solver threads Executor

Food Catalog

Nutrient Requirements

Receipt

Run the solver to view the annual diet cost and selected foods.

Status / Response: