A Discrete Teaching-learning-based optimization algorithm for the green vehicle routing problem.

This paper proposes a discrete teaching-learning-based optimization algorithm to solve the green vehicle routing problem. Firstly, we construct the mathematical model of green vehicle routing problem (GVRP) from the perspective of energy saving and emission reduction, which considers the fuel consumption problem. Then, we propose a discrete teaching-learning-based optimization (DTLBO) algorithm to solve the problem. To further improve the optimization performance of the DTLBO algorithm, we add four local search operators to the algorithm. Finally, we adopt 32 benchmark CVRP instances to test the performance of the proposed algorithm, and the experimental results show the effectiveness of the proposed algorithm.