Driver Schedule Personnalization

At a regional bus depot in northern France, drivers operate under collective agreements that define duty structures, rest times, and rotation rules, but leave limited room for individual preference accommodation. Yet driver satisfaction and schedule acceptance are critical levers for reducing absenteeism, improving retention, and maintaining service quality. The challenge was to move beyond purely constraint-driven scheduling and introduce a preference-aware layer: capturing what drivers actually want (preferred shifts, days off, route types) and weaving those preferences into feasible, operationally sound schedules.

We developed a multi-objective optimization framework that integrates driver preferences directly into the scheduling process, balancing them against operational and regulatory requirements. The approach preserves full compliance with service coverage and labor rules while maximizing aggregate preference satisfaction across the driver population, ensuring that individual gains is achieved while promoting system-wide fairness and efficiency.

• Structured collection and formalization of individual driver preferences (shift types, days off, route affinities)
• Multi-objective scheduling engine balancing preference satisfaction, coverage requirements, and fairness
• Transparent trade-off visualization: planners can see which preferences were honored, deferred, or infeasible
• Human-in-the-loop validation allowing depot managers to review and adjust proposals before publication
• Measurable improvement in schedule acceptance rates and driver engagement (surveys, interviews)