Simultaneous vehicle and crew scheduling for extra urban transports

We present a simultaneous approach to solve the integrated vehicle and crew scheduling problem in an extra urban context. We consider the single depot case with a heterogeneous fleet of vehicles. We propose a constraint based model which is subsequently solved by a Greedy Randomized Adaptive Search Procedure. The construction phase of each initial solution relies on constraint programming techniques, while the local search phase exploits a powerful neighborhood exploration mechanism. The computational experiments conducted on real-world instances show the effectiveness and the flexibility of the approach compared with the classical sequential vehicle and crew scheduling.