This research aims to optimize a VRPTW that incorporates the driver satisfaction factors ‘region consistency’ and ‘workload preference’ while not increasing routing costs too much. The developed measures were optimized for using the ‘Random Allocation’, ‘Driver Assignment’ and ‘Integrated Approach’ methods for various weightings in a multi-objective setting. Driver satisfaction was explicitly optimized in the state-of-the-art VRPTW solver called PyVRP developed by ORTEC. The integrated approach outperformed both the driver assignment and random allocation methods on small and medium sized instances, whereas Driver Assignment performed best on large instances.