HiMCM 2018 · Problem set
The 2018 contest paired a data-heavy ranking problem (which roller coasters are objectively the best?) with a control-and-energy problem (how should a smart home decide when to heat/cool/ventilate?). Both have a strong feature-engineering flavour.
| Contest dates | November 7 – November 20, 2018 (14-day window) |
| Participation | ~730 teams worldwide [illustrative] |
| Problem A | Roller Coaster — objective ranking from a feature dataset |
| Problem B | Cozy Smart House — smart climate-control schedule |
| Official results | 2018 HiMCM results & commentary |
Why 2018 is worth doing. Problem A comes with a real attached dataset
(300+ roller coasters with steel/wood, height, drop, speed, length, inversions, year, etc.) —
it's the closest HiMCM has come to a pure data-science task. Problem B is a great warm-up
for any optimization-over-time problem, including 2021-A.
The two problems
Problem A
Roller Coaster
Given a dataset of hundreds of roller coasters, build an objective ranking. Compare to enthusiast / public votes. Defend your top-10 list to a theme-park magazine.
Open outline →
Problem B
Cozy Smart House
Design a smart-climate-control schedule for a single-family home that balances comfort, energy cost, and outdoor-air health considerations across the year.
Open outline →
Why this year is good practice
- Problem A teaches feature engineering. Highest, fastest, longest aren't obviously commensurate — turning a heterogeneous table into a single score is the entire modelling exercise.
- Problem B teaches dynamic optimization. Day/night, weekday/weekend, winter/summer — the schedule is naturally a small DP or LP.
- Both have clean public data. RCDB.com and EPA / DOE residential energy data are tidy and free.