Fuel-efficient truck platooning by a novel meta-heuristic inspired from ant colony optimisation

Driving trucks in a queue behind each other and in close proximity, called platooning, has been recently under consideration as a novel and promising approach to reduce fuel consumption, which provides environmental and financial benefits. This method works since driving in the slipstream of another vehicle reduces the aerodynamic drag, and as a result, less energy or fuel is consumed. This paper addresses this problem with the realistic assumptions of existing time constraints for trucks to depart from the origin and arrive at their destination, and waiting as well as detour possibility. As this problem is NP-hard even in its very simplified forms, a new meta-heuristic solution methodology inspired from ant colony optimisation is proposed to deal with it. Some sample problems of small to large size are generated and solved with our solution approach. The analysis of results shows the satisfactory performance of this meta-heuristic and its superiority over the exact and our previous approach with genetic algorithm. In addition, we analyse how the final result is affected by changing the main inputs and configurations of the problem.