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Abstract The planning of efficient shift schedules is a key challenge for many service companies whose economic success heavily relies on the efficient employment of personnel. In spite of the recent advances in autonomous driving, mobility services, such as ride pooling, still heavily rely on the use of human drivers and will presumably remain in this category in the near to midterm. As a consequence, shift scheduling of drivers is one of the key success factors in the current industry environment. Determining appropriate shifts that minimize an under- and oversupply of vehicles for all planning periods is a challenging task, since demand can vary heavily over time and the assignment flexibilities are limited due to driver preferences and regulations. In this work, we present a shift scheduling model for ridepooling services. Moreover, we introduce a data generator for instances with realistic properties of a ridepooling service. Using it, we study the effect of different kinds of flexibilities on solution quality.
Berthold et al. (Wed,) studied this question.