Collaborative modes of truck transportation: either swapping body, platooning, or both

Road freight transportation is an essential component of global logistics, persistently challenged by labor shortages, high fuel consumption, and significant carbon emissions. Collaborative transportation technologies such as swapping body and platooning have emerged as efficient strategies to mitigate these issues. This study introduces a novel mixed mode that combines swapping body and platooning strategies, enabling drivers and trucks to cooperate by exchanging trailers and forming platooning convoys, thereby reducing transportation costs and improving overall efficiency. We formulate a generic mixed integer programming model capable of adapting among different truck transportation modes, including traditional, swapping body, platooning, and the proposed mixed mode. To address large-scale practical applications, we propose a variable neighborhood search algorithm with adaptive local search. The performance of the algorithm and the benefits of the proposed mixed mode are validated through comprehensive numerical experiments. Computational results demonstrate that the mixed mode can achieve greater cost savings compared to existing transportation modes while maintaining a higher truck loaded rate and a controllable task delay rate. In particular, the mixed mode demonstrates a synergy effect in some cases, yielding cost savings greater than the sum of its individual components.