Open Access

Srinivasa Ragavan Devanatthan, Stefan Glaser, Klaus Dorer

• Existing approaches solving multi-vehicle pickup and delivery problems with soft time windows typically use common benchmark sets to verify their performance. However, there is a gap from these benchmark sets to real world problems with respect to instance size and problem complexity. In this paper we show that a combination of existing approaches together with improved heuristics is able to dealExisting approaches solving multi-vehicle pickup and delivery problems with soft time windows typically use common benchmark sets to verify their performance. However, there is a gap from these benchmark sets to real world problems with respect to instance size and problem complexity. In this paper we show that a combination of existing approaches together with improved heuristics is able to deal with the instance sizes and complexity of real world problems. The cost savings potential of the heuristics is compared to human dispatching plans generated from the data of a European carrier.…