A data-driven preference learning approach for multi-objective vehicle routing problems in last-mile delivery-Reference-Cited by-同舟云学术

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A data-driven preference learning approach for multi-objective vehicle routing problems in last-mile delivery

Published:2025-05 Issue: Volume:174 Page:105101
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Nourmohammadi Zahra^ORCID,Hu Bohan,Rey David^ORCID,Saberi Meead^ORCID

Publisher

Elsevier BV

Reference115 articles.

1. Dynamic weights in multi-objective deep reinforcement learning;Abels,2019

2. Inverse optimization;Ahuja;Oper. Res.,2001

3. Distance approximation for dynamic waste collection planning;Akkerman,2020

4. An ALNS to optimize makespan subject to total completion time for no-wait flow shops with sequence-dependent setup times;Almeida;TOP,2024

5. A bi-objective green vehicle routing problem with a mixed fleet of conventional and electric trucks: Considering charging power and density of stations;Amiri;Expert Syst. Appl.,2023

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Improved Genetic Algorithm for Solving the Semi-Soft Clustered Vehicle Routing Problem;Applied Sciences;2025-04-27

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