arXiv subjects

Dries Goossens

Publications and source records attributed to Dries Goossens.

12 recordsLinked to original sources

arXiv2026

The Traveling Tournament Problem: An Overview

Over the past 25 years, the Traveling Tournament Problem (TTP) has become one of the most extensively studied optimization problems in sports scheduling. At its core, the TTP seeks to minimize the total travel distance incurred by teams that travel directly between opponents' venues during consecutive away games. The problem originated from the scheduling challenges faced by Major League Baseball, where it was identified as the central computational difficulty. This paper provides a comprehensive overview of the literature on the TTP. We review the principal problem variants and benchmark instances, and summarize the current state of the art in lower bounds, approximation guarantees, and exact and heuristic optimization algorithms. Moreover, we contribute to the continued development of the field by tracking and validating lower and upper bounds, while succeeding the repository originally established by Prof. Michael Trick as part of the RobinX sports timetabling project. Finally, we identify several open questions and outline promising directions for future research.

math.OC↗

arXiv2026

Novel neighborhood structures for incomplete round robin sports tournaments

The incomplete round robin sports tournament format, where each team plays the same number of games but faces only a subset of the other teams, is becoming increasingly popular in both youth and professional competitions. In contrast to conventional round robin tournaments, however, neighborhood structures for scheduling incomplete round robin tournaments have largely remained unexplored. We fill this gap by proposing two novel neighborhood structures and describe them in graph theory terms. One of them introduces a single new game followed by a minimal repair chain, while the other introduces possibly many new games but only affects a single round. The latter is shown to fully connect the solution space. We embed the neighborhoods in an adaptive late acceptance hill climbing algorithm and show that the proposed algorithm obtains high quality and new best solutions for several sets of instances from the literature, thereby empirically confirming the effectiveness of the proposed neighborhoods.

math.OC↗

arXiv2026

The incomplete Traveling Tournament Problem

We present a new problem called the incomplete Traveling Tournament problem, which introduces the well known Traveling Tournament Problem into the realm of incomplete round-robin tournaments. We focus on the case where teams can face each opponent at most once. We give a formal description of this problem and show that it is NP-hard. We first discuss how we can obtain lower bounds and how to strengthen them. Then, we propose two integer programming formulations and compare their LP-relaxations. We also propose a third formulation that assumes that home-away patterns of teams are fixed. We discuss how a recently proposed metaheuristic for incomplete round-robin scheduling can be tailored to our problem. In doing so, we present a novel neighborhood structure and show it fully connects the home-away pattern solution space. Finally, problem instances are proposed, for which we derive lower and upper bounds. We show that these instances are challenging, making the development of efficient algorithms for the incomplete Traveling Tournament problem an interesting direction for future research.

math.OC↗

arXiv2026

On the non-uniformity of the 2026 FIFA World Cup draw

The group stage of a sports tournament is often made more appealing by introducing additional constraints in the group draw that promote an attractive and balanced group composition. For example, the number of intra-regional group matches is minimised in several World Cups. However, under such constraints, the traditional draw procedure may become non-uniform, meaning that the feasible allocations of the teams into groups are not equally likely to occur. Our paper quantifies this non-uniformity of the 2026 FIFA World Cup draw for the official draw procedure, as well as for 47 reasonable alternatives implied by all permutations of the four pots and two group labelling policies. We show why simulating with a recursive backtracking algorithm is intractable, and propose a workable implementation using integer programming. The official draw mechanism is found to be optimal based on four measures of non-uniformity. Nonetheless, non-uniformity can be more than halved if the organiser aims to treat the best teams drawn from the first pot equally.

stat.AP↗

arXiv2025

Fairness, Travel, and Market Potential: An Optimization Framework for NBA Expansion

The National Basketball Association (NBA) is actively considering the addition of two expansion teams, raising the question of how to restructure its conferences and divisions to balance travel efficiency, fairness, and revenue opportunities. This study fills a gap at the intersection of sports operations and strategic league design by providing a quantitative framework for expansion planning. We develop two optimization models: one minimizing total travel distance and another using a Nash Bargaining framework to balance travel burdens while accounting for media market size. Using data from all 30 current franchises and six candidate cities (Seattle, Las Vegas, Montreal, Vancouver, Tampa, and Mexico City), we evaluate 15 pairwise expansion scenarios under alternative season lengths and divisional formats. Results show that while the distance-minimizing model produces geographically tight divisions, the Nash Bargaining model generates more balanced outcomes, particularly for geographically isolated franchises, with only modest efficiency losses. Our study offers a flexible decision support framework for league executives, policymakers, and sports economists. It provides evidence-based insights into how expansion decisions can balance operational efficiency, fairness in competition, and access to major media markets in a multi-billion-dollar sports league.

physics.soc-ph↗

arXiv2025

Evaluating Competitiveness in UEFA's New Champions League Format

Recently, UEFA changed the group stage of its international soccer competitions to an incomplete round robin tournament. Previously, teams were divided into groups, each playing a double round robin tournament with a resulting ranking table. In contrast, the new format has all teams competing in one league, producing a single ranking. We investigate the effect of the new format on the number of competitive matches in the UEFA Champions League. A match is non-competitive if the prize for at least one opponent does not depend on the match outcome, or if there exists an opportunity for both opponents to collude; otherwise, we call a match competitive. Using Monte Carlo simulations, we show that the new format results in more competitive matches than the old format.

physics.soc-ph↗

arXiv2025

The uncertainty of a tournament draw: Insights from the Champions League

The group draw of major sports tournaments implies some uncertainty, with lucky teams often enjoying a substantial unfair advantage. First in the literature, we propose a technique to quantify this draw uncertainty, which, arguably, has an optimal level of zero. Our simulation-based approach requires generating a representative set of random draws to compute the variance of qualifying probabilities for each team. The method is applied to compare draw uncertainty in the former group stage and the current incomplete round-robin league phase of the UEFA Champions League, under both accurate and inaccurate seedings. We also break down the impact of the 2024/25 reform into various components. The new format is found to decrease draw uncertainty, but the reduction is mainly attributable to the inaccurate seeding system used by UEFA. Consequently, the primary benefit of an incomplete round-robin tournament compared to the standard group stage lies in the robustness of its draw uncertainty to the seeding of the teams.

stat.AP↗

arXiv2025

Ranking matters: Does the new format select the best teams for the knockout phase in the UEFA Champions League?

Starting in the 2024/25 season, the Union of European Football Associations (UEFA) has fundamentally changed the format of its club competitions: the group stage has been replaced by a league phase played by 36 teams in an incomplete round robin format. This makes ranking the teams based on their results challenging because teams play against different sets of opponents, whose strengths vary. In this research note, we apply several well-known ranking methods for incomplete round robin tournaments to the 2024/25 UEFA Champions League league phase in order to check the robustness of the official ranking, as well as to call the attention of organizers to the non-trivial issue of ranking in these competitions. Our results show that it is doubtful whether the currently used point-based system provides the best ranking of the teams.

physics.soc-ph↗

arXiv2024

Tournament design: A review from an operational research perspective

Every sport needs rules. Tournament design refers to the rules that determine how a tournament, a series of games between a number of competitors, is organized. This study aims to provide an overview of the tournament design literature from the perspective of operational research. Three important design criteria are discussed: efficacy, fairness, and attractiveness. Our survey classifies the papers discussing these properties according to the main components of tournament design: format, seeding, draw, scheduling, and ranking. We also outline several open questions and promising directions for future research.

physics.soc-ph↗

arXiv2023

Which algorithm to select in sports timetabling?

Any sports competition needs a timetable, specifying when and where teams meet each other. The recent International Timetabling Competition (ITC2021) on sports timetabling showed that, although it is possible to develop general algorithms, the performance of each algorithm varies considerably over the problem instances. This paper provides an instance space analysis for sports timetabling, resulting in powerful insights into the strengths and weaknesses of eight state-of-the-art algorithms. Based on machine learning techniques, we propose an algorithm selection system that predicts which algorithm is likely to perform best when given the characteristics of a sports timetabling problem instance. Furthermore, we identify which characteristics are important in making that prediction, providing insights in the performance of the algorithms, and suggestions to further improve them. Finally, we assess the empirical hardness of the instances. Our results are based on large computational experiments involving about 50 years of CPU time on more than 500 newly generated problem instances.

cs.AI↗

arXiv2023

Fair integer programming under dichotomous and cardinal preferences

One cannot make truly fair decisions using integer linear programs unless one controls the selection probabilities of the (possibly many) optimal solutions. For this purpose, we propose a unified framework when binary decision variables represent agents with dichotomous preferences, who only care about whether they are selected in the final solution. We develop several general-purpose algorithms to fairly select optimal solutions, for example, by maximizing the Nash product or the minimum selection probability, or by using a random ordering of the agents as a selection criterion (Random Serial Dictatorship). We also discuss in detail how to extend the proposed methods when agents have cardinal preferences. As such, we embed the black-box procedure of solving an integer linear program into a framework that is explainable from start to finish. Lastly, we evaluate the proposed methods on two specific applications, namely kidney exchange (dichotomous preferences), and the scheduling problem of minimizing total tardiness on a single machine (cardinal preferences). We find that while the methods maximizing the Nash product or the minimum selection probability outperform the other methods on the evaluated welfare criteria, methods such as Random Serial Dictatorship perform reasonably well in computation times that are similar to those of finding a single optimal solution.

cs.GT↗

arXiv2021

A pessimist's approach to one-sided matching

Inspired by real-world applications such as the assignment of pupils to schools or the allocation of social housing, the one-sided matching problem studies how a set of agents can be assigned to a set of objects when the agents have preferences over the objects, but not vice versa. For fairness reasons, most mechanisms use randomness, and therefore result in a probabilistic assignment. We study the problem of decomposing these probabilistic assignments into a weighted sum of ex-post (Pareto-)efficient matchings, while maximizing the worst-case number of assigned agents. This decomposition preserves all the assignments' desirable properties, most notably strategy-proofness. For a specific class of probabilistic assignments, including the assignment by the Probabilistic Serial mechanism, we propose a polynomial-time algorithm for this problem that obtains a decomposition in which all matchings assign at least the expected number of assigned agents by the probabilistic assignment, rounded down, thus achieving the theoretically best possible guarantee. For general probabilistic assignments, the problem becomes NP-hard. For the Random Serial Dictatorship mechanism, we show that the worst-case number of assigned agents is at least half of the optimal, and that this bound is asymptotically tight. Lastly, we propose a column generation framework for the introduced problem, which we evaluate both on randomly generated data, and on real-world school choice data from the Belgian cities Antwerp and Ghent.

cs.DS↗