Abstract
Simultaneous optimization of vehicles and drivers, creating a mutually compatible set of vehicle and driver schedules within a single optimization,enables the optimization process to achieve lower cost solutions than solutions produced by a sequential process of scheduling vehicles then drivers. This paper presents a case study applying this approach to the network of a large UK logistics provider. The study investigates the impact on solution quality and optimization run time of various techniques that particularly benefit from our approach of solving both scheduling problems simultaneously. These techniques when applied together to the network under study deliver operational cost savings of over 10%.