The finished vehicle routing problem with a heterogeneous transport fleet

This paper presents a new variant of the vehicle routing problem, known as the heterogeneous multi-type fleet vehicle routing problem in finished vehicle logistics (HVRP–FVL), which is modeled and solved. The HVRP–FVL considers various transportation costs, such as highway tolls, labor costs, power costs, time penalty costs, and carbon emissions costs. Moreover, the highway toll is charged based on the transport vehicle model, loading weight, and traveled distance, which adds to the complexity of the problem. The objective of the problem is to minimize the total cost of the vehicle fleet. To solve the HVRP–FVL, a metaheuristic is proposed using a genetic algorithm (GA) metaheuristic. The GA incorporates a dual-chromosome encoding method with adaptive crossover, mutation, and climbing operators to improve computational performance. A case study from a logistics company is used to evaluate the effectiveness of the proposed algorithm, and a series of experiments are conducted. The results demonstrate that the proposed approach performs well and satisfies users in practice. The contributions of the paper are the effective modeling and solution of a natural and complex vehicle routing problem in finished vehicle logistics.