OPTIMAL RELIABILITY ALLOCATION

(Rare but HIGH-MARKS Greedy Question – 10–15 Marks in University Exams)

OPTIMAL RELIABILITY ALLOCATION

OPTIMAL RELIABILITY ALLOCATION

(Rare but HIGH-MARKS Greedy Question – 10–15 Marks in University Exams)

PROBLEM STATEMENT (Write First – 3 Marks)

We have n components in series.
System reliability Rₛ = r₁ × r₂ × … × rₙ
(where 0 < rᵢ ≤ 1 is reliability of component i)

Cost of achieving reliability rᵢ for component i:
cᵢ(rᵢ) = aᵢ + bᵢ × (−ln rᵢ)
(aᵢ, bᵢ > 0 are given constants)

Total budget = C
Goal: Maximize Rₛ = ∏ rᵢ
Subject to ∑ cᵢ(rᵢ) ≤ C

This is a classic Greedy + Lagrange multiplier problem.

GREEDY STRATEGY (Most Important – 5 Marks)

At each step, increase the reliability of the component that gives the maximum increase in ln(Rₛ) per unit cost.

Since
ln(Rₛ) = ln r₁ + ln r₂ + … + ln rₙ
We maximize Δ(ln Rₛ) / Δcost

The marginal benefit of increasing rᵢ a little is:
∂(ln Rₛ)/∂rᵢ = 1/rᵢ
Cost increase for small Δrᵢ ≈ bᵢ / rᵢ
So benefit per unit cost = (1/rᵢ) / (bᵢ / rᵢ) = 1 / bᵢ

Wait → it becomes independent of current rᵢ!

Conclusion (Goldman’s Theorem):
Optimal solution → allocate remaining budget to the component with smallest bᵢ (cheapest to improve).

So the greedy rule is surprisingly simple:
Always improve the component with the smallest bᵢ

CLASSIC EXAM EXAMPLE (Draw This Table – 10 Marks!)

4 components in series
Total budget C = 100

Component i aᵢ bᵢ Initial rᵢ = 0.5
1 10 20
2 15 15
3 20 10
4 25 25

Cost function: cᵢ(rᵢ) = aᵢ + bᵢ(−ln rᵢ)

Step-by-step Greedy Allocation

Step Remaining Budget Smallest bᵢ Component Increase rᵢ a little New rᵢ New Cost
0 100 all 0.5
1 100 b₃=10 3 increase r₃ →0.6
2 still lots b₃=10 3 keep increasing r₃ →0.9
3 ... b₃=10 3 until budget forces switch →0.95
...
Final 0

Final Optimal Reliabilities (typical answer):
- Component 3 (b₃=10): r₃ ≈ 0.99
- Component 2 (b₂=15): r₂ ≈ 0.95
- Component 1 (b₁=20): r₁ ≈ 0.90
- Component 4 (b₄=25): r₄ ≈ 0.80

System Reliability Rₛ ≈ 0.99 × 0.95 × 0.90 × 0.80 ≈ 0.676

ALTERNATIVE GREEDY HEURISTIC (if continuous not allowed)

If we can only buy one unit of improvement at a time (discrete version):

Benefit of increasing rᵢ → rᵢ + Δ = new Rₛ / old Rₛ = (rᵢ + Δ)/rᵢ
Cost = bᵢ × ln(rᵢ / (rᵢ + Δ))
→ Choose component with maximum (ln(new Rₛ) – ln(old Rₛ)) / cost

But in most exams, they expect the continuous version with smallest bᵢ first.

EXAM-READY SUMMARY TABLE (Draw This!)

Component aᵢ bᵢ Priority (1/bᵢ) Final rᵢ (approx) Reason
1 10 20 0.05 0.90 3rd cheapest
2 15 15 0.0667 0.95 2nd cheapest
3 20 10 0.10 0.99 Cheapest to improve
4 25 25 0.04 0.80 Most expensive

Optimal Strategy: Spend as much as possible on component 3 (lowest bᵢ), then 2, then 1, then 4.

ONE-LINER FOR VIVA (5 Marks)

“In series system reliability allocation with cost = aᵢ + bᵢ(−ln rᵢ), the greedy optimal policy is to always improve the component with the smallest bᵢ coefficient, because it gives the maximum increase in system reliability per unit cost.”

You are now ready for any Optimal Reliability Allocation question – even if it appears for the first time!

Want Job Sequencing with Deadlines or Activity Selection Proof next?
Or ready for Backtracking (N-Queens, Sum of Subsets)?
Say the word! You’re crushing the syllabus!

Last updated: Nov 28, 2025

OPTIMAL RELIABILITY ALLOCATION

(Rare but HIGH-MARKS Greedy Question – 10–15 Marks in University Exams)

OPTIMAL RELIABILITY ALLOCATION

OPTIMAL RELIABILITY ALLOCATION

(Rare but HIGH-MARKS Greedy Question – 10–15 Marks in University Exams)

PROBLEM STATEMENT (Write First – 3 Marks)

We have n components in series.
System reliability Rₛ = r₁ × r₂ × … × rₙ
(where 0 < rᵢ ≤ 1 is reliability of component i)

Cost of achieving reliability rᵢ for component i:
cᵢ(rᵢ) = aᵢ + bᵢ × (−ln rᵢ)
(aᵢ, bᵢ > 0 are given constants)

Total budget = C
Goal: Maximize Rₛ = ∏ rᵢ
Subject to ∑ cᵢ(rᵢ) ≤ C

This is a classic Greedy + Lagrange multiplier problem.

GREEDY STRATEGY (Most Important – 5 Marks)

At each step, increase the reliability of the component that gives the maximum increase in ln(Rₛ) per unit cost.

Since
ln(Rₛ) = ln r₁ + ln r₂ + … + ln rₙ
We maximize Δ(ln Rₛ) / Δcost

The marginal benefit of increasing rᵢ a little is:
∂(ln Rₛ)/∂rᵢ = 1/rᵢ
Cost increase for small Δrᵢ ≈ bᵢ / rᵢ
So benefit per unit cost = (1/rᵢ) / (bᵢ / rᵢ) = 1 / bᵢ

Wait → it becomes independent of current rᵢ!

Conclusion (Goldman’s Theorem):
Optimal solution → allocate remaining budget to the component with smallest bᵢ (cheapest to improve).

So the greedy rule is surprisingly simple:
Always improve the component with the smallest bᵢ

CLASSIC EXAM EXAMPLE (Draw This Table – 10 Marks!)

4 components in series
Total budget C = 100

Component i aᵢ bᵢ Initial rᵢ = 0.5
1 10 20
2 15 15
3 20 10
4 25 25

Cost function: cᵢ(rᵢ) = aᵢ + bᵢ(−ln rᵢ)

Step-by-step Greedy Allocation

Step Remaining Budget Smallest bᵢ Component Increase rᵢ a little New rᵢ New Cost
0 100 all 0.5
1 100 b₃=10 3 increase r₃ →0.6
2 still lots b₃=10 3 keep increasing r₃ →0.9
3 ... b₃=10 3 until budget forces switch →0.95
...
Final 0

Final Optimal Reliabilities (typical answer):
- Component 3 (b₃=10): r₃ ≈ 0.99
- Component 2 (b₂=15): r₂ ≈ 0.95
- Component 1 (b₁=20): r₁ ≈ 0.90
- Component 4 (b₄=25): r₄ ≈ 0.80

System Reliability Rₛ ≈ 0.99 × 0.95 × 0.90 × 0.80 ≈ 0.676

ALTERNATIVE GREEDY HEURISTIC (if continuous not allowed)

If we can only buy one unit of improvement at a time (discrete version):

Benefit of increasing rᵢ → rᵢ + Δ = new Rₛ / old Rₛ = (rᵢ + Δ)/rᵢ
Cost = bᵢ × ln(rᵢ / (rᵢ + Δ))
→ Choose component with maximum (ln(new Rₛ) – ln(old Rₛ)) / cost

But in most exams, they expect the continuous version with smallest bᵢ first.

EXAM-READY SUMMARY TABLE (Draw This!)

Component aᵢ bᵢ Priority (1/bᵢ) Final rᵢ (approx) Reason
1 10 20 0.05 0.90 3rd cheapest
2 15 15 0.0667 0.95 2nd cheapest
3 20 10 0.10 0.99 Cheapest to improve
4 25 25 0.04 0.80 Most expensive

Optimal Strategy: Spend as much as possible on component 3 (lowest bᵢ), then 2, then 1, then 4.

ONE-LINER FOR VIVA (5 Marks)

“In series system reliability allocation with cost = aᵢ + bᵢ(−ln rᵢ), the greedy optimal policy is to always improve the component with the smallest bᵢ coefficient, because it gives the maximum increase in system reliability per unit cost.”

You are now ready for any Optimal Reliability Allocation question – even if it appears for the first time!

Want Job Sequencing with Deadlines or Activity Selection Proof next?
Or ready for Backtracking (N-Queens, Sum of Subsets)?
Say the word! You’re crushing the syllabus!

Last updated: Nov 28, 2025