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Short-term work team scheduling models for effective road repair and management

Author

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  • Ching-Hui Tang
  • Shangyao Yan
  • Chia-Wei Chang

Abstract

In this study, we focus on the development of work team routing/scheduling models incorporating stochastic travel and repair times. Robust and expected optimization concepts, combined with a time--space network technique, are used to develop the models. We perform numerical tests based on operational data for Taoyuan County in Taiwan. The test results show the good performance of the models.

Suggested Citation

  • Ching-Hui Tang & Shangyao Yan & Chia-Wei Chang, 2009. "Short-term work team scheduling models for effective road repair and management," Transportation Planning and Technology, Taylor & Francis Journals, vol. 32(3), pages 289-311, April.
  • Handle: RePEc:taf:transp:v:32:y:2009:i:3:p:289-311
    DOI: 10.1080/03081060903017150
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    Cited by:

    1. Nabavi, S.M. & Vahdani, Behnam & Nadjafi, B. Afshar & Adibi, M.A., 2022. "Synchronizing victim evacuation and debris removal: A data-driven robust prediction approach," European Journal of Operational Research, Elsevier, vol. 300(2), pages 689-712.
    2. Moreno, Alfredo & Munari, Pedro & Alem, Douglas, 2019. "A branch-and-Benders-cut algorithm for the Crew Scheduling and Routing Problem in road restoration," European Journal of Operational Research, Elsevier, vol. 275(1), pages 16-34.
    3. Moreno, Alfredo & Alem, Douglas & Gendreau, Michel & Munari, Pedro, 2020. "The heterogeneous multicrew scheduling and routing problem in road restoration," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 24-58.
    4. Souza Almeida, Luana & Goerlandt, Floris & Pelot, Ronald, 2022. "Trends and gaps in the literature of road network repair and restoration in the context of disaster response operations," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    5. Shuanglin Li & Kok Lay Teo, 2019. "Post-disaster multi-period road network repair: work scheduling and relief logistics optimization," Annals of Operations Research, Springer, vol. 283(1), pages 1345-1385, December.

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