Optimizing Two-Truck Platooning With Deadlines

We study a transportation problem where two heavy-duty trucks travel across the national highway from separate origins to destinations, subject individual deadline constraints. Our objective is minimize their total fuel consumption by jointly optimizing path planning, speed and platooning configuration. Such two-truck pervasive in practice yet challenging solve due hard constraints enormous configurations consider. first leverage unique structure significantly simplify optimization present novel formulation. prove that weakly NP-hard admits Fully Polynomial Time Approximation Scheme (FPTAS). The FPTAS can achieve within ratio of $(1+\epsilon)$ optimal (for any notation="LaTeX">$\epsilon >0$ ) with time complexity polynomial size network notation="LaTeX">$1/\epsilon $ . These results are sharp contrast general multi-truck problem, which known be APX-hard repels FPTAS. As still incurs excessive running for large-scale cases, we design an efficient dual-subgradient algorithm solving large-/national- scale instances. It iterative always converges. each iteration only polynomial-time complexity, albeit it requires integer linear programming optimally. characterize condition under generates solution derive posterior performance bound when not met. Extensive simulations based on real-world traces show our joint saves up 24% as compared baseline alternatives.