435. Capacity-Constrained

435.1. Capacity-constrained multi-product newsvendor

Relax two dimensions from basic newsvendor: number of items > 1 and capacity is constrained. Each product has its own demand and cost structure, but they share a budget, warehouse space, or other resource.

Without the constraint, each product is its own newsvendor — 𝑄𝑖∗=𝜇𝑖+𝑧𝑖∗𝜎𝑖 at its own critical ratio CR𝑖=𝐶𝑢𝑖/(𝐶𝑢𝑖+𝐶𝑜𝑖). With a shared constraint, those individual optima may not all be achievable — the constraint forces trade-offs.

435.1.1. Setup

𝑛 products. For each 𝑖:

Constraint:

∑𝑖=1𝑛𝑣𝑖𝑄𝑖≤𝑉

If individual optima already satisfy the constraint, use them. The interesting case is when ∑𝑖𝑣𝑖𝑄𝑖ind>𝑉 — must shrink.

435.1.2. Lagrangian

Maximize total expected profit subject to the capacity constraint:

max𝑄𝑖∑𝑖𝐸[Π𝑖(𝑄𝑖)]s.t.∑𝑖𝑣𝑖𝑄𝑖≤𝑉

where 𝐸[Π𝑖(𝑄𝑖)] is the basic newsvendor expected profit for product 𝑖.

Lagrangian (with multiplier 𝜆≥0):

𝐿=∑𝑖𝐸[Π𝑖(𝑄𝑖)]−𝜆(∑𝑖𝑣𝑖𝑄𝑖−𝑉)

435.1.3. Modified critical ratio

Take 𝜕𝐿/𝜕𝑄𝑖=0 for each 𝑖:

𝜕𝜕𝑄𝑖𝐸[Π𝑖]=𝜆𝑣𝑖

For continuous demand, 𝜕𝐸[Π𝑖]/𝜕𝑄𝑖=(1−𝐹𝑖(𝑄𝑖))𝐶𝑢𝑖−𝐹𝑖(𝑄𝑖)𝐶𝑜𝑖 (from the marginal-analysis derivation in basic newsvendor). Setting equal to 𝜆𝑣𝑖:

(1−𝐹𝑖(𝑄𝑖))𝐶𝑢𝑖−𝐹𝑖(𝑄𝑖)𝐶𝑜𝑖=𝜆𝑣𝑖𝐶𝑢𝑖−𝐹𝑖(𝑄𝑖)(𝐶𝑢𝑖+𝐶𝑜𝑖)=𝜆𝑣𝑖𝐹𝑖(𝑄𝑖∗)=𝐶𝑢𝑖−𝜆𝑣𝑖𝐶𝑢𝑖+𝐶𝑜𝑖

Compare to basic: 𝐹𝑖(𝑄𝑖basic)=𝐶𝑢𝑖/(𝐶𝑢𝑖+𝐶𝑜𝑖). The constraint reduces each product’s effective critical ratio by 𝜆𝑣𝑖/(𝐶𝑢𝑖+𝐶𝑜𝑖) — products that consume more capacity per unit get bigger CR cuts, ordering less.

Effective per-product CR:

CR𝑖(𝜆)=𝐶𝑢𝑖−𝜆𝑣𝑖𝐶𝑢𝑖+𝐶𝑜𝑖

When 𝜆𝑣𝑖≥𝐶𝑢𝑖, the effective CR goes negative — that product is not worth ordering at all given the constraint.

435.1.4. Find 𝜆

𝜆 is chosen so that ∑𝑖𝑣𝑖𝑄𝑖∗(𝜆)=𝑉. One equation, one unknown — bisection works (the LHS is monotone decreasing in 𝜆).

435.1.5. Algorithm

  1. Compute unconstrained 𝑄𝑖basic=𝜇𝑖+Φ−1(CR𝑖basic)𝜎𝑖.
  2. Check ∑𝑖𝑣𝑖𝑄𝑖basic≤𝑉. If yes, done.
  3. Else, find 𝜆>0 such that ∑𝑖𝑣𝑖𝑄𝑖∗(𝜆)=𝑉 (bisection).
  4. Each 𝑄𝑖∗=𝜇𝑖+Φ−1(CR𝑖(𝜆))𝜎𝑖.
Example

Given (2 newspapers competing for budget):

  • Newspaper 1: 𝐷1∼𝒩︀(100,202), 𝑃1=3, 𝐶1=1, 𝑆1=0 → 𝐶𝑢1=2, 𝐶𝑜1=1
  • Newspaper 2: 𝐷2∼𝒩︀(50,152), 𝑃2=5, 𝐶2=2, 𝑆2=0.5 → 𝐶𝑢2=3, 𝐶𝑜2=1.5
  • Capacity (budget): ∑𝑖𝐶𝑖𝑄𝑖≤𝑉 where 𝑉 = $150 (so 𝑣𝑖=𝐶𝑖)

Step 1 — unconstrained per-product newsvendors

CR1=23≈0.667→𝑧1∗≈0.44→𝑄1ind≈100+0.44⋅20=108.8CR2=34.5≈0.667→𝑧2∗≈0.44→𝑄2ind≈50+0.44⋅15=56.6

Budget required: 1⋅108.8+2⋅56.6=108.8+113.2= $222 — exceeds $150 budget. Constraint binds.

Step 2 — solve for 𝜆

Effective critical ratios as a function of 𝜆:

CR1(𝜆)=2−𝜆⋅13,CR2(𝜆)=3−𝜆⋅24.5

Try 𝜆=0.4:

  • CR1(0.4)=1.63≈0.533 → 𝑧1∗≈0.082 → 𝑄1≈100+1.65=101.6
  • CR2(0.4)=2.24.5≈0.489 → 𝑧2∗≈−0.028 → 𝑄2≈50−0.42=49.6
  • Total budget: 1⋅101.6+2⋅49.6=200.8 — still over.

Try 𝜆=0.7:

  • CR1(0.7)=1.33≈0.433 → 𝑧1∗≈−0.168 → 𝑄1≈96.6
  • CR2(0.7)=1.64.5≈0.356 → 𝑧2∗≈−0.370 → 𝑄2≈44.5
  • Total budget: 96.6+89=185.6 — still over.

Try 𝜆=1.0:

  • CR1(1.0)=13≈0.333 → 𝑧1∗≈−0.431 → 𝑄1≈91.4
  • CR2(1.0)=14.5≈0.222 → 𝑧2∗≈−0.764 → 𝑄2≈38.5
  • Total budget: 91.4+77.0=168.4 — close.

Try 𝜆=1.15 (interpolating):

  • CR1(1.15)=0.853≈0.283 → 𝑧1∗≈−0.572 → 𝑄1≈88.6
  • CR2(1.15)=0.74.5≈0.156 → 𝑧2∗≈−1.013 → 𝑄2≈34.8
  • Total budget: 88.6+69.6=158.2 — closer.

Try 𝜆=1.25:

  • CR1(1.25)=0.753=0.25 → 𝑧1∗≈−0.674 → 𝑄1≈86.5
  • CR2(1.25)=0.54.5≈0.111 → 𝑧2∗≈−1.221 → 𝑄2≈31.7
  • Total budget: 86.5+63.4=149.9≈150 ✓
𝜆∗≈1.25

Step 3 — final order quantities

𝑄1∗≈87,𝑄2∗≈32

Both shrink below their individual optima (109, 57). Newspaper 2 shrinks proportionally more because its 𝑣𝑖=2 is twice that of newspaper 1 — the constraint penalizes resource-hungry items more.

Step 4 — compare to unconstrained

  • Unconstrained spend: $222, both products near their individual optimal CR ( 0.667).
  • Constrained spend: $150, both products below their optimal CR — accepting more risk to fit the budget.

The Lagrange multiplier 𝜆∗≈1.25 is the shadow price: each additional dollar of budget would increase total expected profit by approximately $1.25 (until 𝜆 falls back to zero, at which point the constraint stops binding).