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Scheduling sports tournaments by mixed-integer linear programming and a cluster pattern approach : computational implementation using data from the International timetabling competition 2021

Subba, Elias; Stordal, Ole Jacob Lygre
Master thesis
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URI
https://hdl.handle.net/11250/2766790
Date
2021
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  • Master Thesis [4207]
Abstract
The International Timetabling Competition (ITC) has a long tradition of arranging

scientific competitions within the research area of timetabling and its applications. The

2020-2021 edition is devoted to sports timetabling. The aim of ITC 2021 is to stimulate

the development of solution approaches for the construction of round-robin timetables,

meaning that each team plays every other team a fixed number of times. Each instance

consists of a time-constrained double round-robin tournament. Further, the competition

considers two types of constraints: hard constraints represent fundamental properties of

the timetable that can never be violated, while soft constraints represent conditions that

are desirable to satisfy. The resulting problem is to find a timetable the penalties from

violated soft constraints.

In this thesis, we present a heuristic solution approach using a combination of Mixed-

Integer Linear Programming (MILP) and cluster patterns for generating timetables in

sports tournaments. Further, we examine how our solution approach perform on 45

experimental problem instances presented in the ITC 2021.

To the best of out knowledge, this is the first time a approach including clusters patterns,

has been tested on an experimental database.

The computational results show that our solution method is capable of generating a double

round robin timetable for most of the data instances. Further, it provides better results

in a shorter amount of time when compared to running the default MILP model.

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