Scheduling and Timetabling in Sports and Entertainment

  • Michael L. Pinedo


The previous chapter covered the basics of interval scheduling and timetabling. The models considered were relatively simple and their main goal was to provide some insights. In practice, there are many, more complicated applications of interval scheduling and timetabling. For example, there are important applications in sports as well as in entertainment, e.g., the scheduling of games in tournaments and the scheduling of commercials on network television.

This chapter covers basically two topics, namely tournament scheduling and the scheduling of programs on network television. These two topics turn out to be somewhat related. The next section focuses on some theoretical properties of tournament schedules that are prevalent in U.S. college basketball, major league baseball, and European soccer; this section also presents a general framework for tackling the associated optimization problems via integer programming. The third section describes a completely different procedure for dealing with the same problem, namely the constraint programming approach. The fourth section looks at two tournament scheduling problems that are slightly different from the one discussed in the second and third section, and the solution techniques used are based on local search. The fifth section considers a scheduling problem in network television, i.e., how to schedule the programs in order to maximize overall ratings. The subsequent section contains a case study in tournament scheduling; the tournament considered being a college basketball conference. This particular tournament scheduling problem has been tackled with integer programming as well as with constraint programming techniques. The last section discusses the similarities and differences between the different models and approaches considered in this chapter.


Time Slot Constraint Programming Game Assignment Georgia Tech Graph Coloring Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag New York 2009

Authors and Affiliations

  1. 1.Department of Information, Operations, and Management SciencesStern School of Business New York UniversityNew YorkUSA

Personalised recommendations