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The encyclopedia · R&D & Science · Technical decision · 2010–2012

MLB umpires are scheduled by optimization that cuts travel while keeping fairness.

Trick and colleagues used network optimization plus simulated annealing to schedule Major League Baseball umpires, creating the traveling umpire problem.

Major League Baseball

the move

Referee scheduling differs from team scheduling: in Major League Baseball, umpires travel throughout the league and have no home base, so minimizing travel and avoiding overexposure to any one team matter together.

Michael Trick and colleagues created the traveling umpire problem, capturing the major scheduling issues, and solved it with an approach combining network optimization and simulated annealing that respects the league's many constraints.

The method was used to schedule Major League Baseball umpires, and the formalized traveling umpire problem became a widely used benchmark for testing sports-scheduling and heuristic algorithms.

why it works

  • Umpires travel to the work, so travel cost is real
  • A crew can't handle the same team too often
  • Dozens of hard constraints made hand planning brittle
  • The model was actually used to schedule MLB umpires
the payoffOptimize umpire travel and fairness togetherclever

what transfers

Scheduling a workforce that moves like the work needs a joint objective; travel cost and fairness pull against each other, and a model can balance both while respecting every hard rule.

what came after

The work produced a named benchmark problem that researchers still use, and demonstrated that optimization can manage a genuinely complex fairness-plus-efficiency sport scheduling task, though it is best known in the literature as the traveling umpire problem.

references

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