LOG904-162 Scheduling in Sports (Autumn 2020)

About the course

Sports have worldwide appeal. Professional sport leagues involve significant investments and face challenging logistics optimization problems. On the other side, amateur leagues involve less investments, but also require coordination and logistical efforts due to the large number of tournaments and competitors. A key aspect of sporting events is the ability to generate schedules and assign venues that optimize logistic issues and that are seen as fair to all those involved. This is not just restricted to generating the fixtures, but also to other issues such as assigning officials to the games in the competition. Integer programming, constraint programming, metaheuristics, and hybrid methods have been successfully applied to the solution of different variants of this problem. The course starts with an overview of timetabling and scheduling problems in different areas, involving resources such as vehicles (trains, buses), examinations, university courses, personnel (nurses, teachers), games and sports facilities, showing the richness of this field of application and of the techniques presented. The course presents fundamental issues, problem formulations, solution methods, applications, and successful case studies in professional leagues of different sport disciplines such as football, baseball, basketball, cricket, and hockey.

 

Topics covered:

1. Timetabling and scheduling problems: Vehicles (trains, buses), examinations, university courses, personnel (nurses, teachers), games and sports facilities. Models and constraints. Workshop of applications.

 

2. Scheduling in sports: Economical importance of sports. Scheduling problems in sports. Amateur vs professional leagues. Round robin tournaments, objectives and constraints.

 

3. Combinatorial structures: graph theory fundamentals, home and away games. Building schedules from home-away assignments or from timetables, fairness and break minimization, the traveling tournament problem, balanced tournaments, tournaments with referees, carry- over effects, edge colorings, polygon method.

 

4. Metaheuristics in sports scheduling: Greedy algorithms. Neighborhoods, connectivity, local search. Overview of metaheuristics: trajectory-based and population-based methods. Applications of metaheuristics to sports scheduling.

 

5. Integer programming in sports scheduling: Formulations, reformulations, decomposition approaches: first-break-then-schedule and first-schedule-then-break. Applications of integer programming to sports scheduling.

 

6. Sports scheduling in practice: Case studies. Workshop of applications.

The course is connected to the following study programs

• Master of Science in Logistics
• Experience-based Master in Logistics
• Master of Science in Sustainable Energy Logistics
• Exchange programme - Master's level
• Master of Science in Sustainable Transport and Urban Mobility

Recommended requirements

Linear and Integer Programming, basics of Metaheuristics

Forms of teaching and learning

The first goal of this course is to give the students an overview of the class of timetabling and scheduling problems and their broad area of application, including in logistics. The course presents fundamental issues, problem formulations, solution methods, applications, and successful case studies of scheduling in professional leagues of different sport disciplines. In the home assessments, the students will have the opportunity to do some research and to learn in details about applications of their interest.

Examination

Form of assessment: Home assessment with presentation

• Proportion: 50%

• Duration: -

• Grouping: Group

• Grading scale: Letter (A - F)

• Support material: All printed and written supporting material

Form of assessment: Home assessment

• Proportion: 50%

• Duration: -

• Grouping: -

• Grading scale: Letter (A - F)

• Support material: All printed and written supporting material

Syllabus

Some references:

 

1. C.C. Ribeiro,“Sports scheduling: Problems and applications”, International Transactions in

Operational Research 19 (2012), 201-226.

2. G. Kendall, S. Knust, C.C. Ribeiro, and S. Urutia, “Scheduling in sports: An annotated bibliography”, Computers and Operations Research 37 (2010), 1-19.

 

3. D. Briskorn, Sports Leagues Scheduling: Models, Combinatorial Properties, and Optimization

Algorithms, Lecture Notes in Economics and Mathematical Systems 603, Springer, Berlin, 2008

 

4. C.C. Ribeiro, S. Urrutia, and D. de Werra, Combinatorial Models for Sports Scheduling, Springer, Berlin, to appear.