Solving a Real-World Multi-attribute VRP Using a Primal-Based Approach

Through this paper we focus on a real-life combinatorial problem arising in emergent logistics and transportation field. The main objective is to solve a realistic multi-attribute rich Vehicle Routing Problem using a primal-based algorithm embedded in column generation framework. The mathematical model is formulated as a Set Partitioning Problem (SPP) while the subproblem is the shortest path problem with resource constraints (SPPRC). The numerical study was carried out on real instances reaching 140 customers. The successful results show the effectiveness of the method, and highlight its interest.