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JAOT

Food & Beverage Production

Overview

Food and beverage optimization helps manufacturers formulate recipes, plan batches, and schedule production lines to minimize costs while meeting nutritional, quality, and regulatory requirements. From blending animal feed to designing snack bar recipes to scheduling beverage production runs, these problems combine ingredient sourcing decisions with process constraints.

The food industry operates on thin margins, so even small improvements in ingredient utilization or production scheduling can meaningfully impact profitability.

When to Use This

Best for: Food technologists, production planners, and operations managers who need to minimize ingredient costs, meet nutritional targets, or optimize batch scheduling across production lines.

  • Scenario: You need to blend ingredients to meet nutritional or quality specifications at the lowest possible cost, or schedule production runs to maximize throughput
  • Industry: Food processing, beverage manufacturing, animal feed, bakeries, dairy, packaged goods
  • ROI: Typical cost reductions of 3-8% on ingredient spend, plus 10-20% improvement in production line utilization

Step-by-Step Walkthrough

1. Define ingredients and their properties

List available ingredients with their costs per unit, nutritional content (protein, fat, fiber, calories), and availability limits. For example, oats cost $1.20/kg with 13% protein and 7% fat.

2. Set nutritional or quality targets

Define the minimum and maximum levels for each nutrient or quality metric in the final product. A protein bar might require at least 20g protein and no more than 8g fat per serving.

3. Add practical constraints

Include real-world limitations:

  • Ingredient availability or seasonal limits
  • Allergen restrictions (no nuts, gluten-free)
  • Taste or texture requirements (minimum/maximum percentages of specific ingredients)
  • Shelf life considerations

4. Configure the objective

Typically minimize total ingredient cost per batch. Alternatively, maximize nutritional value or minimize calorie count for a health-focused product.

Food & Beverage Optimization in JAOT Builder

5. Review the optimal recipe

The solver returns the ideal mix of ingredients. Verify the recipe makes practical sense (taste, texture) and adjust constraints if needed. Run sensitivity analysis to see how ingredient price changes would affect the recipe.

Example Parameters

import httpx

API_URL = "https://api.jaot.io/api/v2"
headers = {"Authorization": "Bearer ok_live_your_key_here"}

# Minimize cost of a protein bar recipe (per 100g batch)
response = httpx.post(f"{API_URL}/solve", headers=headers, json={
    "variables": [
        {"name": "oats_grams", "type": "continuous", "lb": 0, "ub": 60},
        {"name": "whey_protein_grams", "type": "continuous", "lb": 0, "ub": 40},
        {"name": "honey_grams", "type": "continuous", "lb": 0, "ub": 25},
        {"name": "almonds_grams", "type": "continuous", "lb": 0, "ub": 30},
        {"name": "cocoa_butter_grams", "type": "continuous", "lb": 0, "ub": 15},
    ],
    "objective": {
        "sense": "minimize",
        "coefficients": {
            "oats_grams": 0.0012,
            "whey_protein_grams": 0.008,
            "honey_grams": 0.005,
            "almonds_grams": 0.006,
            "cocoa_butter_grams": 0.009,
        },
    },
    "constraints": [
        {
            "name": "total_weight",
            "coefficients": {
                "oats_grams": 1, "whey_protein_grams": 1,
                "honey_grams": 1, "almonds_grams": 1, "cocoa_butter_grams": 1
            },
            "sense": "==",
            "rhs": 100,
        },
        {
            "name": "min_protein",
            "coefficients": {
                "oats_grams": 0.13, "whey_protein_grams": 0.80,
                "honey_grams": 0.003, "almonds_grams": 0.21, "cocoa_butter_grams": 0.0
            },
            "sense": ">=",
            "rhs": 20,
        },
        {
            "name": "max_fat",
            "coefficients": {
                "oats_grams": 0.07, "whey_protein_grams": 0.01,
                "honey_grams": 0.0, "almonds_grams": 0.49, "cocoa_butter_grams": 0.57
            },
            "sense": "<=",
            "rhs": 12,
        },
    ],
})
result = response.json()

print(f"Minimum cost per bar: ${result['objective_value']:.4f}")
for var in result["variables"]:
    if var["value"] > 0.1:
        print(f"  {var['name']}: {var['value']:.1f}g")

Templates

Diet Optimizer

Minimize ingredient costs while meeting nutritional targets -- ideal for recipe formulation.

Production Planning Optimizer

Schedule food production runs across lines to maximize throughput.

Next Steps