Dynamic Discretization Discovery for the Multidepot Vehicle Scheduling Problem with Trip Shifting

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The dynamic discretization discovery algorithm provides an optimal solution for the multidepot vehicle scheduling problem.
Computational results show this method outperforms both explicit modeling and a branch-and-price algorithm significantly.
The application of trip shifting allows substantial deviations in departure times, enhancing scheduling efficiency.
This strategy effectively resolves the MDVSP-TS for instances with nearly 4,000 trips by avoiding exhaustive trip shift modeling.

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This method demonstrates optimal scheduling improvements in multidepot vehicle challenges, suggesting efficient trip shifting.

Lieshout et al. (2025) studied this question.

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