Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Integrated packing and routing
T2 - A model and its solutions
AU - Liu, Congzheng
AU - Lyu, Jing
AU - Fang, Ke
PY - 2024/12/31
Y1 - 2024/12/31
N2 - 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.
AB - 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.
U2 - 10.1016/j.cor.2024.106790
DO - 10.1016/j.cor.2024.106790
M3 - Journal article
VL - 172
JO - Computers & Operations Research
JF - Computers & Operations Research
M1 - 106790
ER -