A New Approach to Freight Consolidation for a Real-World Pickup-and-Delivery Problem

Abstract

During courier and express providers’ operational scheduling, vehicles are assigned to customer orders. This task is complex, combinatorially comprehensive, and contains aspects that defy modeling within reasonable effort, e.g. due to a lack of structured data. Hence, a fully automated solution cannot be achieved. In practice, human dispatchers often use dialog-oriented decision support systems (DSS). These systems generate recommendations from which the human dispatchers select the most profitable one, while additionally taking into account domain-specific knowledge. Solutions that consolidate the freight of multiple customer orders onto a single vehicle are usually particularly favorable. Generally, consolidating leads to a higher degree of vehicle capacity utilization, which in turn increases cost effectiveness and lowers the resulting environmental damage. We present a new recursive heuristic for this scenario based on the well-known savings algorithm. A central parameter of the algorithm limits the number of interdependent single tours. Through the appropriate setting of this parameter, one can control the results’ complexity and ensure their transparency and acceptance by human dispatchers. Using real-world data benchmarks, we prove the effectiveness of our algorithm empirically.