A Novel Approach to Transform Theoretical Vehicle Routing Problems to Practical Applications

In procurement logistics, manual route planning often leads to inefficiencies such as high costs, congestion, and unbalanced truck arrivals. This paper presents a framework for applying Vehicle Routing Problem (VRP) heuristics to inbound logistics, formulated as an Open VRP with real-world constraints such as vehicle capacities, time windows, and maximum tour duration. Two classical construction heuristics, the Nearest Neighbor Heuristic and the Insertion Heuristic, are adapted and implemented in a configurable tool that enables scenario definition and reproducible evaluation.
The approach is motivated by a case from a German manufacturing company, whose situation served as a reference point for designing fictitious but realistic datasets. The evaluation across 18 scenarios shows that both heuristics generate feasible solutions suitable as baselines for routing decisions. On average, the Insertion Heuristic achieves 13 % higher loading meter utilization (83 % compared to 69 % for the Nearest Neighbor Heuristic) and requires fewer tours, while overall travel times remain nearly identical between the two methods.
Overall, the study demonstrates that heuristic methods provide systematic and time-efficient support for inbound routing in procurement logistics, offering a foundation for practical decision-making and further methodological refinements.