Year: 2025
Type: article
Abstract: This study addresses a routing problem at a last-mile company in Vietnam. It proposes using a machine learning technique-Nearest Neighbor Search-to identify the most similar known solution, which is then used as the initial solution for a branch-and-bound algorithm. Firstly, the machine learning investigated a dataset of 500 pre-solved problems to find solutions for new problems. Then, the solution found is fed to the solver as a hint. The experimental results indicate that the algorithm can retrieve solutions for similar cases in just a few milliseconds. For entirely new problems, the method reduces computation time compared to the traditional branch-and-bound algorithm. This significant improvement in efficiency demonstrates the method’s practical value in real-world logistics operations. The combination of machine learning and classical optimization in this approach shows promise for enhancing decision-making processes in the logistics industry, particularly in scenarios requiring rapid and reliable route planning.
Authors: Nguyen Duc Duy, Lao Khai Kien, Phung Gia Bao
Institution: Ho Chi Minh City University of Technology
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4414886986
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