This paper presents two different models and algorithms for integrated vehicle and crew scheduling in the multiple-depot case. The algorithms are both based on a combination of column generation and Lagrangian relaxation. Furthermore, we compare those integrated approaches with each other and with the traditional sequential one on randomly generated, as well as real-world, data instances for a suburban/extraurban mass transit system. To simulate such a transit system, we propose a new way of randomly generating data instances such that their properties are the same as for our real-world instances.

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ERIM Top-Core Articles
Transportation Science
Erasmus Research Institute of Management

Huisman, D., Freling, R., & Wagelmans, A. (2005). Multiple-depot integrated vehicle and crew scheduling. Transportation Science, 39(4), 491–502. doi:10.1287/trsc.1040.0104