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

Mathematical Modeling and Optimization Approaches for Scheduling the Regular-Season Games of the National Hockey League

RÉSUMÉ : La Ligue nationale de hockey (LNH) est une association sportive professionnelle de hockey sur glace regroupant des équipes du Canada et des États-Unis. Chaque année, la LNH dois compter sur un calendrier de haute qualité concernant des questions économiques et d'équité pour les 1230 matchs de sa saison régulière. Dans cette thèse, nous proposons le premier modèle de programmation linéaire en nombres entiers (PLNE) pour le problème de la planification de ces matchs. Basé sur la littérature scientifique en planification des horaires sportifs, et aussi sur un raisonnement pratique, nous identifions et soulignons des exigences essentielles et des préférences qui doivent être satisfaites par des calendriers de haute qualité pour la LNH. La construction de tels calendriers, tout comme la planification des horaires sportifs en général, s'avère une tâche très difficile qui doit prendre en compte des intérêts concurrents et, dans plusieurs cas, subjectifs. En particulier, les expérimentations numériques que nous décrivons dans cette étude fournissent des évidences solides suggérant qu'une approche basée sur la PLNE est actuellement incapable de résoudre des instances de taille réaliste pour le problème. Pour surmonter cet inconvénient, nous proposons ensuite un algorithme de recherche adaptative à voisinage large (ALNS) qui intègre à la fois des nouvelles stratégies et des heuristiques spécialisées provenant de la littérature scientifique. Afin de tester cette approche, nous générons plusieurs instances du problème. Toutes les instances sont basées sur les calendriers officiels de la LNH et, en particulier, utilisent les dates de matchs à domicile de chaque équipe comme des dates de disponibilité de son aréna. Dans les situations les plus difficiles, la disponibilité des arénas est rare ou est à son minimum. Dans tous les cas, en ce qui concerne les indicateurs de qualité soulevés, l'algorithme ALNS a été capable de générer des calendriers clairement meilleur que leur correspondants adoptés par la LNH. Les résultats obtenus suggèrent que notre approche pourrait certainement permettre aux gestionnaires de la LNH de trouver des calendriers de meilleur qualité par rapport à une variété de nouvelles préférences.----------ABSTRACT : The National Hockey League (NHL) is a major professional ice hockey league composed of 30 teams located throughout the United States and Canada. Every year, the NHL must rely on a high-quality schedule regarding both economic and fairness issues for the 1230 games of its regular season. In this thesis, we propose the first integer linear programming (IP) model for the problem of scheduling those games. Based both on the pertinent sports scheduling literature and on practical reasoning, we identify and point out essential requirements and preferences that should be satisfied by good NHL schedules. Finding such schedules, as many other sports scheduling problems, is a very difficult task that involves several stakeholders with many conflicting, and often subjective, interests. In fact, computational experiments that we describe in this study, provide compelling evidence that an IP approach is currently unable to solve instances of realistic size for the problem. To overcome such drawback, we propose then an Adaptive Large Neighborhood Search (ALNS) algorithm that integrates both novel strategies and specialized heuristics from the scientific literature. To test the approach, we generate instances based on past NHL schedules and on a given number of arena-available dates that are suitable for the home games of each team. In the most challenging instances, availability of arenas is scarce or at its minimum. In all cases, regarding the identified concerns, the ALNS algorithm was able to generate much better schedules than those implemented by the NHL. Results obtained suggest that our approach could certainly identify unnecessary weakness in NHL schedules, makes the NHL managers aware of better schedules with respect to different requirements, and even lead them to consider other desired features they might not have previously taken into account

Sailing League Problems

We describe a class of combinatorial design problems which typically occur in professional sailing league competitions. We discuss connections to mathematical optimization and give suitable boolean quadratic and integer linear optimization problem formulations, as well as further heuristics and restrictions, that can be used to solve sailing league problems in practice. We apply those techniques to three case studies obtained from real sailing leagues and compare the results with used tournament plans.Comment: 22 pages, improved exposition, added additional reference

Graph-Based Sports Rankings

Sports rankings are a widely debated topic among sports fanatics and analysts. Many techniques for systematically generating sports rankings have been explored, ranging from simple win-loss systems to various algorithms. In this report, we discuss the application of graph theory to sports rankings. Using this approach, we were able to outperform existing sports rankings with our new four algorithms. We also reverse-engineered existing rankings to understand the factors that influence them

Ascending-Price Algorithms for Unknown Markets

We design a simple ascending-price algorithm to compute a $(1+\varepsilon)$-approximate equilibrium in Arrow-Debreu exchange markets with weak gross substitute (WGS) property, which runs in time polynomial in market parameters and $\log 1/\varepsilon$. This is the first polynomial-time algorithm for most of the known tractable classes of Arrow-Debreu markets, which is easy to implement and avoids heavy machinery such as the ellipsoid method. In addition, our algorithm can be applied in unknown market setting without exact knowledge about the number of agents, their individual utilities and endowments. Instead, our algorithm only relies on queries to a global demand oracle by posting prices and receiving aggregate demand for goods as feedback. When demands are real-valued functions of prices, the oracles can only return values of bounded precision based on real utility functions. Due to this more realistic assumption, precision and representation of prices and demands become a major technical challenge, and we develop new tools and insights that may be of independent interest. Furthermore, our approach also gives the first polynomial-time algorithm to compute an exact equilibrium for markets with spending constraint utilities, a piecewise linear concave generalization of linear utilities. This resolves an open problem posed by Duan and Mehlhorn (2015).Comment: 33 page

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

Solving Multi-objective Integer Programs using Convex Preference Cones

Esta encuesta tiene dos objetivos: en primer lugar, identificar a los individuos que fueron víctimas de algún tipo de delito y la manera en que ocurrió el mismo. En segundo lugar, medir la eficacia de las distintas autoridades competentes una vez que los individuos denunciaron el delito que sufrieron. Adicionalmente la ENVEI busca indagar las percepciones que los ciudadanos tienen sobre las instituciones de justicia y el estado de derecho en Méxic