HiMCM 2011 · Problem set
An aerospace logistics problem paired with a search-and-rescue planning problem. Problem A asks teams to design a ten-year strategy for resupplying and crewing the International Space Station after the July 2011 retirement of the Space Shuttle — choosing a portfolio of launch vehicles, costing the cargo manifest, and producing a year -by-year schedule through ISS's then-planned 2020 decommissioning. Problem B asks teams to plan a nighttime flashlight search through a wooded park, first for a small lost item and then for a possibly-injured jogger, modeling detection probability and recommending a search pattern under a fixed time budget.
| Contest dates | November 11 – November 21, 2011 (extended weekend window) [illustrative] |
| Participation | ~400 teams, predominantly United States and China [illustrative] |
| Problem A | No More Space Shuttles — ten-year ISS resupply/crew strategy, launch-vehicle portfolio, cost & manifest plan through 2020 |
| Problem B | Search and Find — nighttime penlight search of a wooded park; detection model, sweep-width estimation, time-budgeted plan for a small object and for a lost jogger |
| Official results | 2011 HiMCM problems & commentary |
The two problems
No More Space Shuttles
The Shuttle has flown its last mission. Design a ten-year resupply-and-crew plan for the ISS through 2020: pick a portfolio of launch vehicles (Soyuz, Progress, ATV, HTV, Dragon, Cygnus), match cargo demand to vehicle capacity, schedule launches, and cost the whole program. Deliver a briefing to NASA leadership.
Search and Find
Plan a nighttime search of a wooded park armed only with a penlight. Estimate sweep width and probability of detection, design a search pattern under a fixed time budget, and run two scenarios — a small dropped object versus an injured jogger who may move. Deliver a recommendation to the park ranger.
Why this year is good practice
- Two very different model archetypes. A is a long-horizon logistics & portfolio-optimization problem with hard integer constraints (you cannot launch half a rocket); B is a probabilistic search-theory problem rooted in sweep-width and lateral- range curves. Together they cover capacity planning and detection under uncertainty.
- Real public data. ISS resupply manifests, vehicle payload masses, and unit launch costs are all publicly documented by NASA, ESA, JAXA and Roscosmos. Search- theory benchmarks come from the U.S. Coast Guard's National Search and Rescue Supplement and Koopman's foundational 1956 papers.
- Two non-technical deliverables. A demands a briefing-grade plan that a NASA administrator can defend on Capitol Hill; B demands a one-page operational note the ranger can hand to volunteer searchers. Strong papers nail the executive paragraph and one chart a non-modeler can read in 30 seconds.