A New Property and a Faster Algorithm for Baseball Elimination
SIAM Journal on Discrete Mathematics
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Effective redundant constraints for online scheduling
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Determining the Number of Games Needed to Guarantee an NHL Playoff Spot
CPAIOR '09 Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Hi-index | 0.08 |
A problem of intense interest to many sports fans as a season progresses is whether their favorite team has mathematically clinched a playoff spot; i.e., whether there is no possible scenario under which their team will not qualify. In this paper, we consider the problem of determining when a National Hockey League (NHL) team has clinched a playoff spot. The problem is known to be NP-Complete and current approaches are either heuristic, and therefore not always announced as early as possible, or are exact but do not scale up. In contrast, we present an approach based on constraint programming which is fast and exact. The keys to our approach are the introduction of dominance constraints and special-purpose propagation algorithms. We experimentally evaluated our approach on the past two seasons of the NHL. Our method could show qualification before the results posted in the Globe and Mail, a widely read newspaper which uses a heuristic approach, and each instance was solved within seconds. Finally, we used our solver to examine the effect of scoring models on elimination dates. We found that the scoring model can affect the date of clinching on average by as much as two days and can result in different teams qualifying for the playoffs.