Richard Hoshino

A multi-round generalization of the traveling tournament problem and its application to Japanese baseball

In a double round-robin tournament involving n teams, every team plays 2(n - 1) games, with one home game and one away game against each of the other n - 1 teams. Given a symmetric n by n matrix representing the distances between each pair of home cities, the traveling tournament problem (TTP) seeks to construct an optimal schedule that minimizes the sum total of distances traveled by the n teams as they move from city to city, subject to several natural constraints to ensure balance and fairness. In the TTP, the number of rounds is set at r = 2. In this paper, we generalize the TTP to multiple rounds (r = 2k, for any k [greater-or-equal, slanted] 1) and present an algorithm that converts the problem to finding the shortest path in a directed graph, enabling us to apply Dijkstras Algorithm to generate the optimal multi-round schedule. We apply our shortest-path algorithm to optimize the league schedules for Nippon Professional Baseball (NPB) in Japan, where two leagues of n = 6 teams play 40 sets of three intra-league games over r = 8 rounds. Our optimal schedules for the Pacific and Central Leagues achieve a 25% reduction in total traveling distance compared to the 2010 NPB schedule, implying the potential for considerable savings in terms of time, money, and greenhouse gas emissions.

Scheduling bipartite tournaments to minimize total travel distance

In many professional sports leagues, teams from opposing leagues/conferences compete against one another, playing inter-league games. This is an example of a bipartite tournament. In this paper, we consider the problem of reducing the total travel distance of bipartite tournaments, by analyzing inter-league scheduling from the perspective of discrete optimization. This research has natural applications to sports scheduling, especially for leagues such as the National Basketball Association (NBA) where teams must travel long distances across North America to play all their games, thus consuming much time, money, and greenhouse gas emissions. We introduce the Bipartite Traveling Tournament Problem (BTTP), the interleague variant of the well-studied Traveling Tournament Problem. We prove that the 2n-team BTTP is NP-complete, but for small values of n, a distance-optimal inter-league schedule can be generated from an algorithm based on minimum-weight 4-cycle-covers. We apply our theoretical results to the 12-team Nippon Professional Baseball (NPB) league in Japan, producing a provably-optimal schedule requiring 42950 kilometres of total team travel, a 16% reduction compared to the actual distance traveled by these teams during the 2010 NPB season. We also develop a nearly-optimal inter-league tournament for the 30-team NBA league, just 3.8% higher than the trivial theoretical lower bound.

Exploring the upper bound performance limit of iris biometrics using score calibration and fusion

Researchers now acknowledge that the ultimate goal for biometric technologies to be error-free may never be achieved for any biometric modality. The key interest therefore for any biometric modality is to know its current performance limits. For the iris modality, which is intensively used for trusted traveller programs in many countries, the question of the iris recognition limitations is of particular importance, as it affects security risk mitigation strategies employed by the programs. In this paper, we provide the answer to this question, based on the recent large-scale evaluations of state-of-the-art iris biometrics systems conducted by the National Institute of Standards and Technology (NIST) and the Canada Border Services Agency (CBSA) and two performance-improving post-processing methods developed by the CBSA and its academic partners: one based on score recalibration and the other based on fusion of decisions from multiple systems. Particular emphasis of the paper is on the description of datasets used in iris evaluations and the presentation of the new large-scale iris dataset created for the purpose at the CBSA. The importance of proper evaluation metrics and methodologies used in iris evaluations, including the subject-based analysis, is discussed.

Generating approximate solutions to the traveling tournament problem using a linear distance relaxation

In some domestic professional sports leagues, the home stadiums are located in cities connected by a common train line running in one direction. For these instances, we can incorporate this geographical information to determine optimal or nearly-optimal solutions to the We introduce the Linear Distance Traveling Tournament Problem (LD-TTP), and solve it for We conclude the paper by applying this linear distance relaxation to general (non-linear)