The <i>k</i> -Traveling Repairman Problem with Stochastic Service Request Times

The traveling repairman problem focuses on minimizing total latency, defined as the waiting time experienced by customers after submitting a service request. This problem naturally arises in settings where customer experience is a key objective, particularly in time-sensitive service operations. We address a generalized traveling repairman problem that extends the classical setting by incorporating available probabilistic information on the timing of future requests as well as a more flexible method for measuring the impact of service latency. To account for potential future requests in addition to those known at the time of route planning, we develop a priori routes combined with recourse rules for their execution, aiming to minimize the total expected disutility caused by service latency across all customers. We formulate the problem as a stochastic, path-based traveling repairman problem and solve it using a branch-and-price algorithm, where expected latency is estimated through sample-scenario planning. We then evaluate the performance of our a priori routing approach through a factorial experiment; compare it with alternative routing strategies; and apply these methods to a large-scale, real-world bike-sharing setting. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.0478 .

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Journal
Transportation Science
Published
2025-08-29
DOI
https://doi.org/10.1287/trsc.2023.0478
Primary Topic
Optimization and Search Problems
Type
article
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article

The k -Traveling Repairman Problem with Stochastic Service Request Times

Iman Dayarian, Thomas B. Cassidey
Transportation Science
Optimization and Search Problems
article

The k -Traveling Repairman Problem with Stochastic Service Request Times

Iman Dayarian, Thomas B. Cassidey
article en

Abstract

The traveling repairman problem focuses on minimizing total latency, defined as the waiting time experienced by customers after submitting a service request. This problem naturally arises in settings where customer experience is a key objective, particularly in time-sensitive service operations. We address a generalized traveling repairman problem that extends the classical setting by incorporating available probabilistic information on the timing of future requests as well as a more flexible method for measuring the impact of service latency. To account for potential future requests in addition to those known at the time of route planning, we develop a priori routes combined with recourse rules for their execution, aiming to minimize the total expected disutility caused by service latency across all customers. We formulate the problem as a stochastic, path-based traveling repairman problem and solve it using a branch-and-price algorithm, where expected latency is estimated through sample-scenario planning. We then evaluate the performance of our a priori routing approach through a factorial experiment; compare it with alternative routing strategies; and apply these methods to a large-scale, real-world bike-sharing setting. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.0478 .

Transportation ScienceVol. 60(1)
University of Alabama (US), University of Colorado Colorado Springs (US)
Openalex Percentile: Top 74%
Optimization and Search Problems
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