Subjects · Leaving Cert Applied Maths
Leaving Cert Applied Maths: Dynamic programming & Bellman
How often Dynamic programming & Bellman comes up on the Applied Maths papers, every year it was asked, and questions to try.
HL Asked on 2 of the last 3 Higher Level papers, most recently in 2025. most years
OL Asked on 1 of the last 3 Ordinary Level papers, most recently in 2024.
Quick ones on Dynamic programming & Bellman.
- The cheapest next step is always the best one to take
- Every remaining part of an optimal route is itself optimal
- Every vertex must be visited exactly once on the route
- In increasing order of edge weight
- Forwards from the start, greedily
- Backwards from the final stage
- A step at which a decision is made
- The final destination
- A vertex with the lowest value
Show the answers
(a) Every remaining part of an optimal route is itself optimal
(b) Backwards from the final stage
(c) A step at which a decision is made
Higher Level
Asked on 2 of the last 3 Higher Level papers, most recently in 2025. most years
Every paper, year by year
| Year | Where it came up |
|---|---|
| 2025 | Q6 |
| 2024 | Q8 |
| 2023 | Not asked |
Links open the State Examinations Commission’s paper for that year.
More Dynamic programming & Bellman questions
Dynamic programming & Bellman, 2 marks
A machine can be kept or replaced at the start of each year. In the dynamic programming model, these are the…?
- States
- Stages
- Actions
Show the answer
Actions
The years are the stages, the machine's age is the state, and keep or replace are the actions. Each action has a cost and moves you to a new age in the next stage.
Dynamic programming & Bellman, 3 marks
Why does working backwards through the stages save work in dynamic programming?
- It can skip the last stage of the network
- Each state's best value is found once and reused
- It only follows the cheapest arcs backwards
Show the answer
Each state's best value is found once and reused
Once you know the best value from every state in a stage, earlier stages just add one arc to it. You never have to list and total every complete route.
Dynamic programming & Bellman, 3 marks
A staged network offers 3 choices at each of 4 decisions. How many complete routes are there?
- 81
- 12
- 64
Show the answer
81
Routes multiply: 3 × 3 × 3 × 3 = 3⁴ = 81. Bellman's backward pass avoids totalling all 81; it compares only a few options at each state.
Ordinary Level
Asked on 1 of the last 3 Ordinary Level papers, most recently in 2024.
Every paper, year by year
| Year | Where it came up |
|---|---|
| 2025 | Not asked |
| 2024 | Q5 |
| 2023 | Not asked |
Links open the State Examinations Commission’s paper for that year.
More Dynamic programming & Bellman questions
Dynamic programming & Bellman, 2 marks
Dynamic programming solves a staged network by working…
- Forwards, choosing the cheapest edge each time
- At random through the stages
- Backwards from the final stage
Show the answer
Backwards from the final stage
You start at the destination and find the best value from each state to the end, stage by stage, until you reach the start.
Dynamic programming & Bellman, 2 marks
Can dynamic programming find the route with the greatest total profit?
- Only if all profits are equal
- Yes, take the largest value at each state
- No, it only finds shortest distances
Show the answer
Yes, take the largest value at each state
The backward method works the same way for a maximum: at each state choose the action giving the biggest value to the end.
Dynamic programming & Bellman, 3 marks
Bellman's principle of optimality says that…
- The rest of an optimal route is also optimal
- The shortest edge is always in the best route
- The first choice alone decides the best route
Show the answer
The rest of an optimal route is also optimal
Whatever state you reach, the remaining decisions of an optimal policy must be optimal from that state. This is why working backwards gives the best overall route.
Other Applied Maths topics
- Calculus & variable acceleration
- Connected particles & pulleys
- Constant acceleration (suvat)
- Dijkstra's algorithm
- Displacement & velocity graphs
- First-order difference equations
- Forces & Newton's laws
- Friction & inclined planes
- Graphs & network terminology
- Horizontal circular motion
- Loans, savings & finance models
- Matrices & adjacency
- Minimum spanning trees
- Momentum & direct collisions
- Oblique collisions
- Projectile motion
- Recurrence relations & differences
- Reducing second-order DEs
- Resisted motion & drag
- Second-order difference equations
- Separable differential equations
- The modelling cycle & assumptions
- Vectors & the dot product
- Vertical circular motion
- Dimensional analysis
- Project scheduling & critical path
- Work, energy & conservation
- Greedy vs dynamic algorithms
- Hooke's law & elastic energy