What This Tool Does

The Backpacking Resupply Optimizer helps backpackers plan lightweight, nutritionally complete food resupply boxes. Given your trip duration, calorie target, and store type, it selects a basket of shelf-stable, no-cook foods that minimizes total pack weight while meeting dietary reference intake targets — the same trade-off you face when deciding whether to carry almonds or instant mashed potatoes.

Datasets

Optimization Model

Decision Variables

For each candidate food i, the model has two variables:

• g_i ≥ 0 — grams of food i to pack
• y_i ∈ {0, 1} — binary indicator: 1 if food i is selected at all (used when food diversity is > 0)

When diversity is zero, only continuous g_i variables are used and the problem is solved as a linear program (LP) with GLOP. When diversity > 0, binary variables are added and the problem becomes a mixed-integer program (MIP) solved with SCIP. Both solvers are from Google OR-Tools.

Objective Function

The default objective is maximum calorie density — equivalently, minimum total weight for a fixed calorie target:

minimize   Σ g_i

Carrying fewer grams to hit the same calorie goal means a lighter pack. Because calorie density varies by food (nuts ~7 kcal/g, dried fruit ~3 kcal/g, instant meals ~4 kcal/g), the optimizer gravitates toward calorie-dense foods unless constrained by nutrition or diversity.

Other available objectives:

• Lowest Cost — minimize Σ price_i × g_i / 100
• Most Diverse — maximize a category-spread score
• Max Protein / Fiber / Vitamin C / Iron / Vitamin D — maximize that nutrient per gram

Constraints

• Calorie target: total calories must fall within ±3% of calories_per_day × days
• Nutrient minimums (optional, from DRI): for each nutrient with a non-zero scale, Σ (nutrient_i / 100) × g_i ≥ DRI_min × scale. If a nutrient is physically unachievable from the available food set, the constraint is automatically relaxed and a warning is shown.
• Nutrient maximums: upper bounds from the Dietary Reference Intakes (e.g. max iron 45mg/day) are enforced to prevent unsafe megadosing.
• Per-food cap: no single food may contribute more than a fraction of total calories (40% at diversity=0, relaxing toward 100% at diversity=1 to give the minimum-foods constraint room to work).
• Category calorie cap: when diversity > 0, no food category (e.g. Nuts & Seeds) may supply more than (1 − 0.55×diversity) of total calories.
• Minimum distinct foods (MIP only): Σ y_i ≥ min_foods, where min_foods = round(diversity × 20), capped at the candidate set size. Each selected food must also contribute at least ~50 kcal (enforced via g_i ≥ min_serving × y_i) so the binary variables correspond to meaningful portions.
• Perishability filter: foods with days_without_refrigeration < trip_days are excluded from the candidate set entirely.

Dietary Reference Intakes (DRI)

Nutrient minimums are scaled from DRI values computed for a 70 kg adult per day × number of trip days. The "Nutrition Profile" setting applies a multiplier to each nutrient's minimum:

• Optimal — full DRI for protein, fiber, calcium, iron, vitamin C, vitamin D; 75% for potassium, B12, zinc, magnesium, folate; 50% for choline
• Reduced — 25–50% of DRI for most nutrients; zero for zinc, magnesium, folate, choline
• None — no nutrient constraints applied
• Custom — per-nutrient sliders

Prices

All prices are estimates derived from FoodAPS purchase observations, adjusted to 2025 dollars using category-specific food CPI series from the BLS (Consumer Price Index, U.S. City Average, All Urban Consumers). The median observed price per 100g is multiplied by a category-specific inflation factor; a fallback of $0.50/100g × 1.45 (overall food-at-home inflation) is applied where no observed price exists.

Inflation multipliers by food category (2013 average to December 2025):

• Cereals & Grains, Bars & Snacks: ×1.35 (CUUR0000SAF11)
• Dairy & Cheese: ×1.39 (CUUR0000SAF114)
• Meat, Poultry, Seafood: ×1.23 (CUUR0000SAF113)
• Fruits, Vegetables, Dried Fruit: ×1.27 (CUUR0000SAF116)
• Nuts, Oils, Condiments, Beverages, Sweets: ×1.24 (CUUR0000SEFJ)
• All other / fallback: ×1.45 (CUUR0000SAF1)

These multipliers are recomputed each time inflate_prices.py is run against the live BLS public API.

Limitations

• FoodAPS prices are from 2012–2013 and are inflation-adjusted to 2025 dollars using BLS food CPI series, but category-level indices may not capture variation within a category (e.g. organic vs. conventional).
• Only ~1,260 of 4,400 foods have observed purchase prices; the rest use the $0.50/100g fallback.
• Package sizes are derived from typical FoodAPS purchase quantities and are approximate.
• The perishability lookup is a conservative estimate based on food category, not specific products.
• Nutrient values are per-100g averages across food preparations and may not reflect the specific product you buy.