Block-matrix-based approach for the vehicle routing problem with transportation type selection under an uncertain environment

The vehicle routing problem has become a fundamental part of supply chains in competitive environments. Many studies have been conducted on the uncertain vehicle routing problem to improve transportation plans. However, few have concentrated on the selection of transportation type under uncertain environments. In this study, a novel vehicle routing model that considers transportation type selection between milk-run and cross-dock strategies under uncertain environments with fuzzy travel time is proposed. Furthermore, a novel block-matrix-based approach for the transportation type selection is presented to explore optimal transportation plans in an intuitive, reasonable, effective and efficient form. An extended biogeography-based optimization algorithm is proposed to derive an optimal transportation plan by extending the migration and mutation operators, and introducing a novel self-adaptive mutation rate and a secondary mutation operator. Finally, simulation experiments are performed to validate the effectiveness and practicality of this approach in solving the proposed model.