Heterogeneous Green Vehicle Routing Problem with Different Customer Service Requirements

The Green Vehicle Routing Problem (GVRP) is a challenging combinatorial optimization problem to optimize delivery routes while minimizing adverse environmental impacts. A Heterogeneous Green Vehicle Routing Problem with Different Customer Service Requirements (HGVRP-CSR) is presented in this paper, and it deals with three objectives to minimize vehicle traveling cost, and carbon emission cost and maximize customer satisfaction simultaneously. In this work, we propose a mixed integer linear programming model for HGVRP-CSR and present a Hybrid Variable Neighborhood Search (HVNS) combining two stages of heuristic operations. In HVNS, a Hungarian algorithm and a hierarchical clustering are conducted in the initialization stage to generate better initial solutions, and to enhance its search capabilities, four Neighborhood transformation operations are adopted, i.e., single-point insertion, two-point exchange, two-segment exchange, and 2-opt. The comprehensive experiments are performed on problems of different sizes to verify the effectiveness and efficiency of HVNS. The comparative results show that HVNS is more effective than the other two algorithms.