Mock problems
Five original problems written in HiMCM style, each with a rubric you can use to self-grade. The problems cover the recurring patterns from the past archive — multi-criteria decision, forecasting, population dynamics, optimization/routing, and impact modeling.
How to use these. Pick one. Block off a weekend (or, for the longest ones, four days).
Don't read the solution sketch first — work the problem solo or with one or two teammates. Write a 5–10
page partial paper. Then open the rubric and the solution sketch. Compare. Note what you missed.
The mocks
Decision-style
M1
Choosing a Future Lunar Base Location
Multi-criteria scoring on landing sites — energy, water, science, terrain, comms.
Forecasting
M2
Modeling the Streaming Video Energy Footprint
Forecast HVS / streaming demand and its carbon implications under 3 scenarios.
Population / spread
M3
Spotted Lanternfly Containment Strategy
Model invasive insect spread + design a county-level containment program.
Optimization / routing
M4
Last-Mile Drone Delivery for a Suburb
Hybrid truck+drone delivery network with battery and weather constraints.
Impact modeling
M5
Fast-Fashion's Hidden Water Bill
Estimate apparel-supply-chain water footprint and design a label-based intervention.
Self-assessment rubric
After writing your mock paper, score yourself on each row, then total.
| Section | Looking for | Out of |
|---|---|---|
| Summary sheet | Standalone; contains results not just methodology; concrete numbers | 10 |
| Problem understanding | Restated in own words; key elements identified; flowchart if helpful | 5 |
| Assumptions & justifications | Each tied to model; sources cited; "used in" pointer | 10 |
| Variables / notation | Compact table with units; symbols defined when first used | 5 |
| Model development | Choice motivated; math defined; solution method explained; visual aids | 25 |
| Application of model | ≥2–3 scenarios per problem statement; results tabulated; differences explained | 15 |
| Sensitivity analysis | Multiple parameters varied; method explained; conclusions drawn | 10 |
| Strengths & limitations | Both present; specific; honest about weaknesses | 5 |
| Conclusion & recommendations | Concrete, actionable, supported by analysis | 5 |
| Non-technical letter / article | Different from summary; right audience; clear ask | 5 |
| References / formatting / clean writing | Citations present; page numbers; no name leaks; ≤25 pages | 5 |
| Total | 100 | |
Rough interpretation: 80+ ≈ Meritorious; 60–80 ≈ Honorable Mention; below 60 ≈ Successful Participant. First mocks will probably score 40–60 — that's normal, and that's exactly what we're here to improve.
How to simulate contest conditions
- Lock the timer. Pick a window (e.g., a Friday evening through Sunday night). Don't extend.
- No outside humans. No tutoring, no asking the math teacher, no Discord. Books and the web are fine.
- Cite as you go. Don't bookmark "I'll add the citations later." You won't.
- Limit AI use. If you'd use it in the real contest, use it now too — and write the AI Report appendix.
- Submit a real PDF. Export it. Open it in another viewer. Make sure pages, headers, and math all look right.
After the mock
- Self-score against the rubric. Be honest.
- Read the linked solution sketch. Note three things you missed and three things you did well.
- Write a short retrospective: what would you change about your process next time? (Time allocation, who did what, when did you get stuck.)
- Pick the weakest rubric area and study it before the next mock.