Abstract
This paper introduces the two-level vehicle routing and loading problem (2L-VRLP), an innovative model integrating the two-level bin packing and vehicle routing problems to address real-world logistics challenges that require simultaneous packing and transportation decisions. By capturing the essence of dual-level packing (boxes onto pallets, pallets onto vehicles) and optimising vehicle routing, the 2L-VRLP offers an integrated framework that outperforms traditional separated models, demonstrating superior solutions that align closely with practical logistics operations. We propose a set of heuristic algorithms tailored for the 2L-VRLP’s unique requirements and explore automated algorithm selection using an artificial neural network (ANN), marking a step towards incorporating machine learning in logistics optimisation. This work not only showcases the 2L-VRLP model’s potential to enhance logistics management but also sets the groundwork for future research and applications in this domain.
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