Jong Hun Woo

628 total citations
51 papers, 423 citations indexed

About

Jong Hun Woo is a scholar working on Industrial and Manufacturing Engineering, Safety, Risk, Reliability and Quality and Control and Systems Engineering. According to data from OpenAlex, Jong Hun Woo has authored 51 papers receiving a total of 423 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Industrial and Manufacturing Engineering, 6 papers in Safety, Risk, Reliability and Quality and 5 papers in Control and Systems Engineering. Recurrent topics in Jong Hun Woo's work include Advanced Manufacturing and Logistics Optimization (22 papers), Maritime Ports and Logistics (15 papers) and Optimization and Packing Problems (12 papers). Jong Hun Woo is often cited by papers focused on Advanced Manufacturing and Logistics Optimization (22 papers), Maritime Ports and Logistics (15 papers) and Optimization and Packing Problems (12 papers). Jong Hun Woo collaborates with scholars based in South Korea, Sweden and United Kingdom. Jong Hun Woo's co-authors include Young-Joo Song, Jong Gye Shin, Yongkuk Jeong, Jong-Ho Nam, Jong-Moo Lee, Dong Kun Lee, Kwang Hee Ko, So Hyun Nam, Haoyu Zhu and Hee Chang Yoon and has published in prestigious journals such as Sustainability, Applied Sciences and Engineering Applications of Artificial Intelligence.

In The Last Decade

Jong Hun Woo

43 papers receiving 395 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jong Hun Woo South Korea 13 296 44 35 29 29 51 423
Yongkuk Jeong South Korea 11 201 0.7× 14 0.3× 14 0.4× 17 0.6× 29 1.0× 44 302
Lars Magne Nonås Norway 9 156 0.5× 41 0.9× 65 1.9× 20 0.7× 90 3.1× 11 311
Donald C. Sweeney United States 9 199 0.7× 27 0.6× 22 0.6× 24 0.8× 17 0.6× 21 427
Annalisa Santolamazza Italy 10 176 0.6× 14 0.3× 90 2.6× 11 0.4× 16 0.6× 15 396
Katarina S. Vukadinović Serbia 11 235 0.8× 36 0.8× 70 2.0× 48 1.7× 63 2.2× 21 428
Waqar Ahmed Khan Hong Kong 12 97 0.3× 12 0.3× 30 0.9× 58 2.0× 10 0.3× 23 364
Rodrigo Acuña-Agost France 9 136 0.5× 10 0.2× 38 1.1× 41 1.4× 7 0.2× 17 377
Alejandro Escudero-Santana Spain 11 177 0.6× 16 0.4× 15 0.4× 11 0.4× 25 0.9× 47 326
Jiang Xi China 10 143 0.5× 64 1.5× 48 1.4× 6 0.2× 19 0.7× 51 360
Zheyi Tan China 14 321 1.1× 47 1.1× 26 0.7× 16 0.6× 77 2.7× 35 447

Countries citing papers authored by Jong Hun Woo

Since Specialization
Citations

This map shows the geographic impact of Jong Hun Woo'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 Jong Hun Woo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jong Hun Woo more than expected).

Fields of papers citing papers by Jong Hun Woo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jong Hun Woo. 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 Jong Hun Woo. The network helps show where Jong Hun Woo may publish in the future.

Co-authorship network of co-authors of Jong Hun Woo

This figure shows the co-authorship network connecting the top 25 collaborators of Jong Hun Woo. A scholar is included among the top collaborators of Jong Hun Woo 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 Jong Hun Woo. Jong Hun Woo 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.
Woo, Jong Hun, et al.. (2025). Solving quay wall allocation problems based on deep reinforcement learning. Engineering Applications of Artificial Intelligence. 150. 110598–110598.
2.
3.
Woo, Jong Hun, et al.. (2025). Scheduling optimization of hull block assembly line using constraint programming and discrete-event simulation. International Journal of Naval Architecture and Ocean Engineering. 17. 100675–100675.
4.
Nam, So Hyun, et al.. (2024). An analysis of pipe spool supply chain in shipbuilding using 2-stage queuing model and discrete event simulation. International Journal of Naval Architecture and Ocean Engineering. 16. 100611–100611.
5.
Woo, Jong Hun, et al.. (2024). Forecasting shipbuilding demand using shipping market modeling: A case study of LNGC. International Journal of Naval Architecture and Ocean Engineering. 16. 100616–100616. 4 indexed citations
6.
Woo, Jong Hun, et al.. (2024). Simulation-based deep reinforcement learning for multi-objective identical parallel machine scheduling problem. International Journal of Naval Architecture and Ocean Engineering. 16. 100629–100629.
7.
Woo, Jong Hun, et al.. (2023). Locating algorithm of steel stock area with asynchronous advantage actor-critic reinforcement learning. Journal of Computational Design and Engineering. 11(1). 230–246. 3 indexed citations
8.
Kwak, Dong Hoon, et al.. (2022). Optimization of long-term planning with a constraint satisfaction problem algorithm with a machine learning. International Journal of Naval Architecture and Ocean Engineering. 14. 100442–100442. 8 indexed citations
9.
Nam, So Hyun, et al.. (2022). Development of Des Application for Factory Material Flow Simulation With Simpy. 2022 Winter Simulation Conference (WSC). 1545–1556. 3 indexed citations
10.
Nam, So Hyun, et al.. (2021). Development of the Reinforcement Learning-based Adaptive Scheduling Algorithm for Panel Block Shop. Seoul National University Open Repository (Seoul National University). 26(2). 81–92. 2 indexed citations
11.
Woo, Jong Hun, Haoyu Zhu, Dong Kun Lee, Hyun Chung, & Yongkuk Jeong. (2021). Assessment Framework of Smart Shipyard Maturity Level via Data Envelopment Analysis. Sustainability. 13(4). 1964–1964. 4 indexed citations
12.
Zhu, Haoyu & Jong Hun Woo. (2021). Hybrid NHPSO-JTVAC-SVM Model to Predict Production Lead Time. Applied Sciences. 11(14). 6369–6369. 9 indexed citations
13.
Jeong, Yongkuk, et al.. (2018). Shipyard Block Logistics Simulation Using Process-centric Discrete Event Simulation Method. Journal of Ship Production and Design. 34(2). 168–179. 17 indexed citations
14.
Woo, Jong Hun, et al.. (2017). A Research on Simulation Framework for the Advancement of Supplying Management Competency. Journal of Ship Production and Design. 33(1). 60–79. 4 indexed citations
15.
Jeong, Yongkuk, et al.. (2017). Shipyard Block Logistics Simulation Using Process-centric Discrete Event Simulation Method. Journal of Ship Production and Design. 3 indexed citations
16.
Woo, Jong Hun. (2014). Research on the HSE Application with Smart Device and Biometrics. 19(2). 157–168. 1 indexed citations
17.
Woo, Jong Hun, Jong-Ho Nam, & Kwang Hee Ko. (2014). Development of a simulation method for the subsea production system. Journal of Computational Design and Engineering. 1(3). 173–186. 18 indexed citations
18.
Song, Young-Joo & Jong Hun Woo. (2013). New shipyard layout design for the preliminary phase & case study for the green field project. International Journal of Naval Architecture and Ocean Engineering. 5(1). 132–146. 5 indexed citations
19.
Woo, Jong Hun, et al.. (2010). Development of the Decision-Making System for the Ship Block Logistics Based on the Simulation. Journal of Ship Production and Design. 26(4). 290–300. 9 indexed citations
20.
Song, Young-Joo, Jong Hun Woo, & Jong Gye Shin. (2009). Research on a simulation-based ship production support system for middle-sized shipbuilding companies. International Journal of Naval Architecture and Ocean Engineering. 1(2). 70–77. 11 indexed citations

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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2026