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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Deep reinforcement learning for the dynamic and uncertain vehicle routing problem
Weixu Pan, Shi Qiang Liu
Applied Intelligence (2022) Vol. 53, Iss. 1, pp. 405-422
Closed Access | Times Cited: 65

Showing 1-25 of 65 citing articles:

Smart Distribution in E-Commerce: Harnessing Machine Learning and Deep Learning Approaches for Improved Logistics
Krishna Kumaar Ragothaman
International Journal of Computational and Experimental Science and Engineering (2025) Vol. 11, Iss. 1
Open Access | Times Cited: 2
Machine Learning to Solve Vehicle Routing Problems: A Survey
Aigerim Bogyrbayeva, Meraryslan Meraliyev, Taukekhan Mustakhov, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 6, pp. 4754-4772
Closed Access | Times Cited: 14
Dynamic maintenance scheduling approach under uncertainty: Comparison between reinforcement learning, genetic algorithm simheuristic, dispatching rules
Marcelo Luis Ruiz Rodríguez, Sylvain Kubler, Jérémy Robert, et al.
Expert Systems with Applications (2024) Vol. 248, pp. 123404-123404
Open Access | Times Cited: 10
Scheduling optimization of electric ready mixed concrete vehicles using an improved model-based reinforcement learning
Zhengyi Chen, Hao Wang, Baoyi Wang, et al.
Automation in Construction (2024) Vol. 160, pp. 105308-105308
Closed Access | Times Cited: 9
Energy-optimal routing for electric vehicles using deep reinforcement learning with transformer
Mengcheng Tang, Weichao Zhuang, Bingbing Li, et al.
Applied Energy (2023) Vol. 350, pp. 121711-121711
Closed Access | Times Cited: 22
Memory-efficient Transformer-based network model for Traveling Salesman Problem
Hua Yang, MingHao Zhao, Lei Yuan, et al.
Neural Networks (2023) Vol. 161, pp. 589-597
Closed Access | Times Cited: 19
Multi-start team orienteering problem for UAS mission re-planning with data-efficient deep reinforcement learning
Dong Ho Lee, Jaemyung Ahn
Applied Intelligence (2024) Vol. 54, Iss. 6, pp. 4467-4489
Open Access | Times Cited: 7
Integrating Machine Learning Into Vehicle Routing Problem: Methods and Applications
Reza Shahbazian, Luigi Di Puglia Pugliese, Francesca Guerriero, et al.
IEEE Access (2024) Vol. 12, pp. 93087-93115
Open Access | Times Cited: 4
Transportation Mode Selection Using Reinforcement Learning in Simulation of Urban Mobility
Mehmet Bilge Han Taş, Kemal Özkan, İnci Sarıçiçek, et al.
Applied Sciences (2025) Vol. 15, Iss. 2, pp. 806-806
Open Access
Two-stage graph attention networks and Q-learning based maintenance tasks scheduling
Xiaoyong Gao, Peng Diao, Yuning Yang, et al.
Applied Intelligence (2025) Vol. 55, Iss. 5
Closed Access
Multi-strategy ant colony optimization with k-means clustering algorithm for capacitated vehicle routing problem
Zhaojun Zhang, Simeng Tan, Jia-Jia Qin, et al.
Cluster Computing (2025) Vol. 28, Iss. 3
Closed Access
An Optimized Method for Solving the Green Permutation Flow Shop Scheduling Problem Using a Combination of Deep Reinforcement Learning and Improved Genetic Algorithm
Yongxin Lu, Yiping Yuan, Yasenjiang Jiarula, et al.
Mathematics (2025) Vol. 13, Iss. 4, pp. 545-545
Open Access
The Dynamic Traveling Salesman Problem with Time-Dependent and Stochastic travel times: A deep reinforcement learning approach
Dawei Chen, Christina Imdahl, David Lai, et al.
Transportation Research Part C Emerging Technologies (2025) Vol. 172, pp. 105022-105022
Open Access
Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Survey
Zefang Zong, Jingwei Wang, Tao Feng, et al.
ACM Transactions on Knowledge Discovery from Data (2025)
Open Access
Harnessing heterogeneous graph neural networks for Dynamic Job-Shop Scheduling Problem solutions
Chien‐Liang Liu, P.S. Weng, Chun-Jan Tseng
Computers & Industrial Engineering (2025), pp. 111060-111060
Closed Access
Dynamic fleet management of waterborne vessels with mixed passenger and parcel services
Heisuke Miyoshi, Yimeng Zhang, Shadi Sharif Azadeh, et al.
Deleted Journal (2025) Vol. 2, Iss. 1
Open Access
Integrating NSGA-II and Q-learning for Solving the Multi-objective Electric Vehicle Routing Problem with Battery Swapping Stations
Anouar Haddad, Takwa Tlili, Nadia Dahmani, et al.
International Journal of Intelligent Transportation Systems Research (2025)
Closed Access
Real-time pickup and delivery scheduling for inter-island logistics using waterborne AGVs
Huarong Zheng, Jun Tian, Anqing Wang, et al.
Applied Intelligence (2025) Vol. 55, Iss. 7
Closed Access
Dynamic Routing in Urban Logistics: A Comprehensive Review of AI, Real-Time Data, and Sustainability Impacts
Hilman Rismanto, Loso Judijanto
Sinergi International Journal of Logistics (2025) Vol. 3, Iss. 2, pp. 68-79
Closed Access
Dynamic UAV Inspection Boosted by Vehicle Collaboration Under Harsh Conditions in the IoT Realm
Dai Hou, Zhaohui Yao, Bo Jin, et al.
Applied Sciences (2025) Vol. 15, Iss. 9, pp. 4671-4671
Open Access
Rüppell’s fox optimizer: A novel meta-heuristic approach for solving global optimization problems
Malik Braik, Heba Al-Hiary
Cluster Computing (2025) Vol. 28, Iss. 5
Closed Access
A bi-level programming methodology for decentralized mining supply chain network design
Q. Zhang, Shi Qiang Liu, Andrea D’Ariano, et al.
Expert Systems with Applications (2024) Vol. 250, pp. 123904-123904
Closed Access | Times Cited: 3
A hierarchical deep reinforcement learning method for solving urban route planning problems under large-scale customers and real-time traffic conditions
Yuanyuan Li, Qingfeng Guan, Jun Feng Gu, et al.
International Journal of Geographical Information Science (2024), pp. 1-24
Closed Access | Times Cited: 3
Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning
Yimeng Zhang, Rudy R. Negenborn, Bilge Atasoy
Transportation Research Part C Emerging Technologies (2023) Vol. 156, pp. 104355-104355
Open Access | Times Cited: 8
Bi-objective bi-level optimization for integrating lane-level closure and reversal in redesigning transportation networks
Qiang Zhang, Shi Qiang Liu, Andrea D’Ariano
Operational Research (2023) Vol. 23, Iss. 2
Closed Access | Times Cited: 7
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