A matheuristic algorithm for the vehicle routing problem with cross-docking

This paper studies the integration of vehicle routing problem with cross-docking (VRPCD). The aim is to find a set routes deliver products from suppliers customers through cross-dock facility, such that operational and transportation costs are minimized, without violating capacity time horizon constraints. A two-phase matheuristic based on column generation proposed. first phase focuses generating feasible candidate in both pickup delivery processes by implementing an adaptive large neighborhood search algorithm. destroy repair operators used order explore space. second solving partitioning model determine final solution. proposed tested available benchmark VRPCD instances compared state-of-the-art algorithms. Experimental results show competitiveness as it able improve best known solutions for 80 obtain same remaining 10 instances, average improvement 12.6%. On new larger our maintains its solution quality within acceptable CPU times outperforms pure ALNS We also explicitly analyze performance considering time.