The Machine Learning and Traveling Repairman Problem

  • Theja Tulabandhula
  • Cynthia Rudin
  • Patrick Jaillet
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6992)


The goal of the Machine Learning and Traveling Repairman Problem (ML&TRP) is to determine a route for a “repair crew,” which repairs nodes on a graph. The repair crew aims to minimize the cost of failures at the nodes, but the failure probabilities are not known and must be estimated. If there is uncertainty in the failure probability estimates, we take this uncertainty into account in an unusual way; from the set of acceptable models, we choose the model that has the lowest cost of applying it to the subsequent routing task. In a sense, this procedure agrees with a managerial goal, which is to show that the data can support choosing a low-cost solution.


machine learning traveling repairman integer programming uncertainty generalization bound constrained linear function classes 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Theja Tulabandhula
    • 1
  • Cynthia Rudin
    • 1
  • Patrick Jaillet
    • 1
  1. 1.Massachusetts Institute of TechnologyCambridgeUSA

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