How to Optimize Monthly Oil Purchases and Production for Maximum Profit
Given spot and futures prices for vegetable and non‑vegetable oils, refining capacity limits, storage constraints, and a required product hardness range, this model determines the optimal monthly buying, refining, and inventory decisions that maximize profit for a food‑oil manufacturer over a six‑month horizon.
Problem Description
Manufacturer needs to refine several raw oils and blend them to produce a sellable food product. Two categories of oils are required: vegetable oils (VEG 1, VEG 2) and non‑vegetable oils (OIL 1, OIL 2, OIL 3).
Spot and futures prices (USD/ton) for each oil by month (January–June) are given:
January: VEG1 110, VEG2 120, OIL1 130, OIL2 110, OIL3 115
February: VEG1 130, VEG2 130, OIL1 110, OIL2 90, OIL3 115
March: VEG1 110, VEG2 140, OIL1 130, OIL2 100, OIL3 95
April: VEG1 120, VEG2 110, OIL1 120, OIL2 120, OIL3 125
May: VEG1 100, VEG2 120, OIL1 150, OIL2 110, OIL3 105
June: VEG1 90, VEG2 100, OIL1 140, OIL2 80, OIL3 135
Additional considerations:
Final food product sells for $150 per ton.
Vegetable and non‑vegetable oils are refined on separate production lines.
Refining capacity is limited to 200 t of vegetable oil and 250 t of non‑vegetable oil per month.
No waste in refining; total refined oil equals total refined product.
Refining cost is negligible.
Storage limit per oil type is 1000 t; storage cost is $ ? per ton per month (value omitted).
Food product hardness must be between 3 and 6. Hardness is a linear blend of oil hardnesses: VEG1 = 8.8 VEG2 = 6.1 OIL1 = 2.0 OIL2 = 4.2 OIL3 = 5.0
Initial inventory: 500 t of each oil at the beginning of January; also 500 t of each oil must be on hand at the end of June.
Mathematical Model
Sets
T: set of months.
V: set of vegetable oils.
N: set of non‑vegetable oils.
O: set of all oil types (V ∪ N).
Parameters
p = 150 USD/t (selling price of final product).
s₀ᵢ: initial storage of oil i (500 t).
sᴛᵢ: target storage of oil i at end of horizon (500 t).
cᵢₜ: purchase price of oil i in month t (from the price tables).
hᵢ: hardness of oil i (values above).
γᵥ = 200 t (vegetable refining capacity per month).
γₙ = 250 t (non‑vegetable refining capacity per month).
H_min = 3, H_max = 6 (hardness limits).
k: storage cost per ton per month (not specified).
Decision Variables
xᵢₜ: amount of oil i purchased in month t.
yᵢₜ: amount of oil i refined (consumed) in month t.
zᵢₜ: inventory of oil i at end of month t.
qₜ: amount of final product produced in month t.
Objective
Maximize total profit over the planning horizon:
<code>∑ₜ (p·qₜ – ∑ᵢ cᵢₜ·xᵢₜ – k·zᵢₜ)</code>Constraints
Inventory balance: zᵢ₍ₜ₋₁₎ + xᵢₜ = yᵢₜ + zᵢₜ for all i, t.
Refining capacity: ∑_{i∈V} yᵢₜ ≤ γᵥ and ∑_{i∈N} yᵢₜ ≤ γₙ for all t.
Hardness: H_min ≤ (∑ᵢ hᵢ·yᵢₜ) / qₜ ≤ H_max for all t.
Mass balance: qₜ = ∑ᵢ yᵢₜ for all t.
Initial and final inventory: zᵢ₀ = s₀ᵢ, zᵢ_{|T|} = sᴛᵢ.
The model determines the optimal monthly purchase and refining plan that maximizes profit while respecting capacity, storage, and product quality constraints.
Model Perspective
Insights, knowledge, and enjoyment from a mathematical modeling researcher and educator. Hosted by Haihua Wang, a modeling instructor and author of "Clever Use of Chat for Mathematical Modeling", "Modeling: The Mathematics of Thinking", "Mathematical Modeling Practice: A Hands‑On Guide to Competitions", and co‑author of "Mathematical Modeling: Teaching Design and Cases".
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