The machine learning and traveling repairman problem

Published

Conference Paper

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. © 2011 Springer-Verlag.

Full Text

Duke Authors

Cited Authors

  • Tulabandhula, T; Rudin, C; Jaillet, P

Published Date

  • October 31, 2011

Published In

Volume / Issue

  • 6992 LNAI /

Start / End Page

  • 262 - 276

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

International Standard Book Number 13 (ISBN-13)

  • 9783642248726

Digital Object Identifier (DOI)

  • 10.1007/978-3-642-24873-3_20

Citation Source

  • Scopus