Breaks, cuts, and patterns

Wegeneralize the concept of a break by considering pairs of arbitrary rounds.Weshow that a set of homeaway patterns minimizing the number of generalized breaks cannot be found in polynomial time, unless P = NP. When all teams have the same break set, the decision version becomes easy; optimizing remains NP-hard.status: publishe

Round-robin tournaments with minimum number of breaks and two teams per club

We study round-robin tournaments for 2n teams. Here n is either interpreted as the number of clubs, each having two teams, or the number of strength groups with two teams each. For even n we give a construction of a single round-robin tournament for 2n teams with 2n - 2 breaks, where the teams of the same club have complementary home-away patterns and play against each other in the first round. If the pairs of teams are strength groups, then a cyclic permutation of the constructed schedule results in a group-balanced tournament

Scheduling sport tournaments using constraint logic programming

We tackle the problem of scheduling the matches of a round robin tournament for a sport league. We formally define the problem, state its computational complexity, and present a solution algorithm using a two-step approach. The first step is the creation of a tournament pattern and is based on known graph-theoretic results. The second one is a constraint-based depth-first branch and bound procedure that assigns actual teams to numbers in the pattern. The procedure is implemented using the finite domain library of the constraint logic programming language eclipse. Experimental results show that, in practical cases, the optimal solution can be found in reasonable time, despite the fact that the problem is NP-complete

An instance data repository for the round-robin sports timetabling problem

The sports timetabling problem is a combinatorial optimization problem that consists of creating a timetable that defines against whom, when and where teams play games. This is a complex matter, since real-life sports timetabling applications are typically highly constrained. The vast amount and variety of constraints and the lack of generally accepted benchmark problem instances make that timetable algorithms proposed in the literature are often tested on just one or two specific seasons of the competition under consideration. This is problematic since only a few algorithmic insights are gained. To mitigate this issue, this article provides a problem instance repository containing over 40 different types of instances covering artificial and real-life problem instances. The construction of such a repository is not trivial, since there are dozens of constraints that need to be expressed in a standardized format. For this, our repository relies on RobinX, an XML-supported classification framework. The resulting repository provides a (non-exhaustive) overview of most real-life sports timetabling applications published over the last five decades. For every problem, a short description highlights the most distinguishing characteristics of the problem. The repository is publicly available and will be continuously updated as new instances or better solutions become available

Particle Swarm Algorithm for Improved Handling of the Mirrored Traveling Tournament Problem

In this study, we used a particle swarm optimization (PSO) algorithm to address a variation of the non-deterministic polynomial-time NP-hard traveling tournament problem, which determines the optimal schedule for a double round-robin tournament, for an even number of teams, to minimize the number of trips taken. Our proposed algorithm iteratively explored the search space with a swarm of particles to find near-optimal solutions. We also developed three techniques for updating the particle velocity to move towards optimal points, which randomly select and replace row and column parameters to find candidate positions close to an optimal solution. To further optimize the solution, we calculated the particle cost function, an important consideration within the problem conditions, for team revenues, fans, and media. We compared our computation results with two well-known meta-Heuristics: a genetics algorithm utilizing a swapping method and a Greedy Randomized Adaptive Search Procedure Iterated Local Search algorithm heuristic on a set of 20 teams. Ultimately, the PSO algorithm generated solutions that were comparable, and often superior, to the existing well-known solutions. Our results indicate that our proposed algorithm could aid in reducing the overall budget expenditures of international sports league organizations, which could enable significant monetary savings and increase profit margins

Do you Believe He Can Fly? Royce White and Reasonable Accommodations Under the Americans with Disabilities Act for NBA Players with Anxiety Disorder and Fear of Flying

This Article examines the legal ramifications of Royce White, a basketball player with general anxiety disorder and obsessive compulsive disorder, playing in the NBA. White\u27s conditions cause him to have a fear of flying, thus making it difficult to play in the NBA. This subject is without precedent in sports law and, because of the unique aspects of an NBA playing career, lacks clear analogy to other employment circumstances. This dispute also illuminates broader legal and policy issues in the relationship between employment and mental illness.This Article argues that White would likely fail in a lawsuit against an NBA team and the NBA under the Americans with Disabilities Act. Case law disfavors recognition of his conditions as workplace disabilities, and even if a court recognizes them as such, there appears to be no reasonable accommodation that doesn\u27t necessitate him flying. This Article also contends that if White cannot adequately resolve his health issues, it would be advisable for him -- and the NBA and Players\u27 Association -- to find creative resolutions. Such an approach would be far preferable to litigation. One such approach could be loaning White\u27s employment to another pro basketball league where all or almost all games are played within driving distance. In that circumstance, he could develop his game against talented pro basketball players and, hopefully, gradually overcome his health issues. The Israel Super Basketball League (Ligat Winner Sal) is one such league. During time in another league, White\u27s NBA employment rights could remain with an NBA team. This Article also insists the NBA and Players\u27 Association take mental health policies more seriously, especially as increasing rates of Americans are diagnosed with mental illness. For years, the NBA and Players\u27 Association have focused on physical health policies while largely ignoring mental health

Proceedings of Mathsport international 2017 conference

Proceedings of MathSport International 2017 Conference, held in the Botanical Garden of the University of Padua, June 26-28, 2017. MathSport International organizes biennial conferences dedicated to all topics where mathematics and sport meet. Topics include: performance measures, optimization of sports performance, statistics and probability models, mathematical and physical models in sports, competitive strategies, statistics and probability match outcome models, optimal tournament design and scheduling, decision support systems, analysis of rules and adjudication, econometrics in sport, analysis of sporting technologies, financial valuation in sport, e-sports (gaming), betting and sports

Solving Challenging Real-World Scheduling Problems

This work contains a series of studies on the optimization of three real-world scheduling problems, school timetabling, sports scheduling and staff scheduling. These challenging problems are solved to customer satisfaction using the proposed PEAST algorithm. The customer satisfaction refers to the fact that implementations of the algorithm are in industry use. The PEAST algorithm is a product of long-term research and development. The first version of it was introduced in 1998. This thesis is a result of a five-year development of the algorithm. One of the most valuable characteristics of the algorithm has proven to be the ability to solve a wide range of scheduling problems. It is likely that it can be tuned to tackle also a range of other combinatorial problems. The algorithm uses features from numerous different metaheuristics which is the main reason for its success. In addition, the implementation of the algorithm is fast enough for real-world use.Siirretty Doriast