No description, website, or topics provided.
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
Gephi
Matlab
Results
docs
src
LICENSE
README.md

README.md

TournamentAllocationProblem

This repository is related to a thesis work at the Politecnico di Torino. Full thesis is available here.

The interactive graph visualizer for the 2017 Grand Slams tournaments is available.

Thesis Abstract

Single-elimination tournaments are a popular type of tournament among sports, more specifically in tennis. Despite the current state-of-the-art procedures prevent seeded players - or highest rated opponents - from matching in early rounds, match repetitions among other players are possible, even in tournaments very close in terms of time. Therefore, the allocation process for non-seeded players plays a fundamental role in avoiding match repetitions and in increasing the diversity of matches. The thesis develops a methodology for enforcing fairness in single-elimination tennis tournaments in terms of a reduction of match repetitions in consecutive different tournaments, without significantly altering the draw procedure. The considered tournament allocation problem amounts to solving a clustering problem by means of mathematical programming. Several results and solutions are provided for real-life instances related to Grand Slams in 2017 by exploiting the potential of an Integer Programming solver. Moreover, a greedy approach to generate quantitatively good solutions is presented, along with two heuristics. Full tournament simulations are performed to assess the quality of presented methodologies. Among the results, appreciable improvements are obtained for both the expected number of match repetitions and a related measure of fairness. Benchmarks between heuristics, the greedy algorithm, and the optimal solutions are presented. An important outcome is related to the quality of solutions built with the greedy algorithm. Some techniques of data visualization are implemented to highlight the obtained results.

License

MIT License

Copyright (c) 2018 Gabriele Dragotto

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.