Improving Driver Satisfaction
Exploring cost effects of optimization on workload preference and region consistency in a VRPTW
Q.W.J. van Gulik (TU Delft - Electrical Engineering, Mathematics and Computer Science)
D.C. Gijswijt – Mentor (TU Delft - Discrete Mathematics and Optimization)
Alexander Heinlein – Graduation committee member (TU Delft - Numerical Analysis)
Lotte Berghman – Mentor (Ortec B.V.)
Tom Bruinink – Graduation committee member (Ortec B.V.)
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Abstract
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.