Scheduling the Australian football league

Generating a schedule for a professional sports league is an extremely demanding task. Good schedules have many benefits for the league, such as higher attendance and TV viewership, lower costs, and increased fairness. The Australian Football League is particularly interesting because of an unusual competition format integrating a single round robin tournament with additional games. Furthermore, several teams have multiple home venues and some venues are shared by multiple teams. This paper presents a 3-phase process to schedule the Australian Football League. The resulting solution outperforms the official schedule with respect to minimizing and balancing travel distance and breaks, while satisfying more requirements

Referee assignment in the Chilean football league using integer programming and patterns

This article uses integer linear programming to address the referee assignment problem in the First Division of the Chilean professional football league. The proposed approach considers balance in the number of matches each referee must officiate, the frequency of each referee being assigned to a given team, the distance each referee must travel over the course of a season, and the appropriate pairings of referee experience or skill category with the importance of the matches. Two methodologies are studied, one traditional and the other a pattern-based formulation inspired by the home-away patterns for scheduling season match calendars. Both methodologies are tested in real-world and experimental instances, reporting results that improve significantly on the manual assignments. The pattern-based formulation attains major reductions in execution times, solving real instances to optimality in just a few seconds, while the traditional one takes anywhere from several minutes to more than an hour.Fil: Alarcón, Fernando. Universidad de Chile; ChileFil: Duran, Guillermo Alfredo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Guajardo, Mario. Norwegian School of Economics; Norueg

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

Towards prevention of sportsmen burnout : Formal analysis of sub-optimal tournament scheduling

Funding Statement: The authors are grateful to the Deanship of Scientific Research at King Saud University, Saudi Arabia for funding this work through the Vice Deanship of Scientific Research Chairs: Chair of Pervasive and Mobile Computing.Peer reviewedPublisher PD

Fixture-scheduling for the Australian Football League using a Multi-objective Evolutionary Algorithm

AFL football is a team sport that entertains millions and contributes a huge amount of money to the Australian economy. Scheduling games in the AFL is difficult, as a number of different, often conflicting, factors must be considered. In this paper, we propose the use of a multi-objective evolutionary algorithm for determining such a schedule. We detail the technical details needed to apply a multi-objective evolutionary algorithm to this problem and report on experiments that show the effectiveness of this approach. Comparison with actual schedules used in the AFL demonstrates that this approach could make a useful contribution

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

Time Relaxed Round Robin Tournament and the NBA Scheduling Problem

This dissertation study was inspired by the National Basketball Association regular reason scheduling problem. NBA uses the time-relaxed round robin tournament format, which has drawn less research attention compared to the other scheduling formats. Besides NBA, the National Hockey League and many amateur leagues use the time-relaxed round robin tournament as well. This dissertation study is the first ever to examine the properties of general time-relaxed round robin tournaments. Single round, double round and multiple round time-relaxed round robin tournaments are defined. The integer programming and constraint programming models for those tournaments scheduling are developed and presented. Because of the complexity of this problem, several decomposition methods are presented as well. Traveling distance is an important factor in the tournament scheduling. Traveling tournament problem defined in the time constrained conditions has been well studied. This dissertation defines the novel problem of time-relaxed traveling tournament problem. Three algorithms has been developed and compared to address this problem. In addition, this dissertation study presents all major constraints for the NBA regular season scheduling. These constraints are grouped into three categories: structural, external and fairness. Both integer programming and constraint programming are used to model these constraints and the computation studies are presente

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

A hybrid constraint-based programming approach to design a sports tournament scheduling

We investigate the problem of sports tournament scheduling as reflected in the quality of tournament schedule in University Utara Malaysia (UUM). The background of the sports tournament problems that inefficiency of the human scheduler, time-consuming task and unfairness among the athletes that need to be solved gives direction and motivation in investigating the problem of scheduling the sports tournament. Subsequently,previous work related to the problem is discussed. Thus, we present an innovative hybrid of a constraint-based algorithm and a neighbourhood search, which is an exploration into alternative and improved methodology in the problem of sports tournament scheduling with special multiple constraints. A scheduling system is then developed. As a result, fair distribution of break or rest times and game venues among the competing teams are achieved in our objectives. The sports tournament scheduling system assists and improves the sports events management through high quality schedule as compared with the current human scheduler, which consider rest period, day and time preferences and venue availability. Thus, this sophisticated algorithm provides the feasible, optimum, efficient and quick solution