Dujuan Wang

4.2k total citations
132 papers, 3.0k citations indexed

About

Dujuan Wang is a scholar working on Industrial and Manufacturing Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Dujuan Wang has authored 132 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Industrial and Manufacturing Engineering, 21 papers in Computer Networks and Communications and 17 papers in Artificial Intelligence. Recurrent topics in Dujuan Wang's work include Scheduling and Optimization Algorithms (33 papers), Optimization and Search Problems (20 papers) and Vehicle Routing Optimization Methods (20 papers). Dujuan Wang is often cited by papers focused on Scheduling and Optimization Algorithms (33 papers), Optimization and Search Problems (20 papers) and Vehicle Routing Optimization Methods (20 papers). Dujuan Wang collaborates with scholars based in China, Hong Kong and United Kingdom. Dujuan Wang's co-authors include Yunqiang Yin, T.C.E. Cheng, Yanzhang Wang, Yaochu Jin, Chin‐Chia Wu, Sutong Wang, Shaoze Cui, Zhiwu Li, Feng Liu and Shuenn‐Ren Cheng and has published in prestigious journals such as European Journal of Operational Research, Journal of Business Research and Frontiers in Immunology.

In The Last Decade

Dujuan Wang

121 papers receiving 2.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dujuan Wang China 31 1.3k 610 449 227 217 132 3.0k
Zhibin Jiang China 32 1.6k 1.3× 325 0.5× 274 0.6× 642 2.8× 141 0.6× 229 3.6k
Yves Crama Belgium 31 1.3k 1.0× 608 1.0× 382 0.9× 99 0.4× 129 0.6× 124 3.1k
Yunqiang Yin China 41 3.0k 2.4× 772 1.3× 1.4k 3.0× 385 1.7× 462 2.1× 198 5.2k
Jean‐Paul Watson United States 38 528 0.4× 373 0.6× 579 1.3× 157 0.7× 97 0.4× 131 6.3k
Shih-Wei Lin Taiwan 46 3.5k 2.7× 1.5k 2.5× 831 1.9× 209 0.9× 237 1.1× 227 7.1k
Daryl Essam Australia 42 1.1k 0.9× 2.3k 3.7× 264 0.6× 720 3.2× 177 0.8× 197 4.8k
David L. Woodruff United States 36 1.4k 1.1× 363 0.6× 265 0.6× 661 2.9× 333 1.5× 99 5.6k
Martine Labbé Belgium 35 1.6k 1.2× 271 0.4× 404 0.9× 163 0.7× 101 0.5× 168 3.8k
Liang Qi China 31 1.4k 1.1× 450 0.7× 265 0.6× 360 1.6× 55 0.3× 214 3.5k
H. Edwin Romeijn United States 34 922 0.7× 358 0.6× 248 0.6× 671 3.0× 34 0.2× 123 3.5k

Countries citing papers authored by Dujuan Wang

Since Specialization
Citations

This map shows the geographic impact of Dujuan Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dujuan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dujuan Wang more than expected).

Fields of papers citing papers by Dujuan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dujuan Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dujuan Wang. The network helps show where Dujuan Wang may publish in the future.

Co-authorship network of co-authors of Dujuan Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Dujuan Wang. A scholar is included among the top collaborators of Dujuan Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dujuan Wang. Dujuan Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Dujuan, et al.. (2025). Multi-agent deep reinforcement learning-based truck-drone collaborative routing with dynamic emergency response. Transportation Research Part E Logistics and Transportation Review. 195. 103974–103974. 7 indexed citations
2.
3.
Wang, Dujuan, Shilin Wang, Liping Wang, et al.. (2025). Intratumoral Stenotrophomonas Maltophilia in Breast Cancer: Unraveling the Interplay with Hormone Receptors and Impact on Tumor Immunity. International Journal of Biological Sciences. 21(3). 974–988. 5 indexed citations
4.
Wang, Dujuan, et al.. (2025). SMR-agents: Synergistic medical reasoning agents for zero-shot medical visual question answering with MLLMs. Information Processing & Management. 63(1). 104297–104297.
5.
Ignatius, Joshua, et al.. (2025). Robust multi-period blood inventory routing under multiple uncertainties. European Journal of Operational Research. 328(1). 137–161.
6.
Wang, Dujuan, Qingyou Xia, Yi Feng, & T.C.E. Cheng. (2025). Unravelling the effects of two inconsistencies on online review helpfulness: Evidence from TripAdvisor. Decision Support Systems. 193. 114450–114450.
7.
Wang, Dujuan, et al.. (2025). A prediction interval framework-based spatial–temporal convolution block network for traffic demand prediction. Transportation Research Part E Logistics and Transportation Review. 204. 104426–104426. 1 indexed citations
8.
Wang, Dujuan, et al.. (2024). Uplift modeling and its implications for appointment date prediction in attended home delivery. Decision Support Systems. 185. 114303–114303. 1 indexed citations
9.
Wang, Dujuan, et al.. (2024). A scenario-based robust approach for joint planning of multi-blood product logistics and multi-casualty type evacuation. Transportation Research Part E Logistics and Transportation Review. 184. 103493–103493. 8 indexed citations
10.
Yin, Yunqiang, et al.. (2024). Two-stage recoverable robust optimization for an integrated location–allocation and evacuation planning problem. Transportation Research Part B Methodological. 182. 102906–102906. 16 indexed citations
11.
Wang, Dujuan, et al.. (2024). Exact solution method for vehicle-and-drone cooperative delivery routing of blood products. Computers & Operations Research. 164. 106559–106559. 14 indexed citations
12.
Yin, Yunqiang, et al.. (2023). Wasserstein distance‐based distributionally robust parallel‐machine scheduling. Omega. 120. 102896–102896. 13 indexed citations
13.
Wang, Dujuan, Qi Wang, Yunqiang Yin, & T.C.E. Cheng. (2023). Optimization of ride-sharing with passenger transfer via deep reinforcement learning. Transportation Research Part E Logistics and Transportation Review. 172. 103080–103080. 22 indexed citations
14.
Yin, Yunqiang, et al.. (2023). Robust vehicle routing with drones under uncertain demands and truck travel times in humanitarian logistics. Transportation Research Part B Methodological. 174. 102781–102781. 49 indexed citations
15.
Chu, Feng, et al.. (2023). An exact algorithm for the home health care routing and scheduling with electric vehicles and synergistic-transport mode. Annals of Operations Research. 16 indexed citations
16.
Wang, Sutong, et al.. (2023). Expanded feature space-based gradient boosting ensemble learning for risk prediction of type 2 diabetes complications. Applied Soft Computing. 144. 110451–110451. 10 indexed citations
17.
Wang, Liping, Dujuan Wang, Liu Yang, et al.. (2022). Cuproptosis related genes associated with Jab1 shapes tumor microenvironment and pharmacological profile in nasopharyngeal carcinoma. Frontiers in Immunology. 13. 989286–989286. 61 indexed citations
18.
Wang, Dujuan, et al.. (2022). Robust optimization for the electric vehicle pickup and delivery problem with time windows and uncertain demands. Computers & Operations Research. 151. 106119–106119. 27 indexed citations
19.
Liu, Ronghua, Lin Lin, & Dujuan Wang. (2016). Antimicrobial prophylaxis in caesarean section delivery. Experimental and Therapeutic Medicine. 12(2). 961–964. 19 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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