Tae‐Eog Lee

3.8k total citations
128 papers, 2.9k citations indexed

About

Tae‐Eog Lee is a scholar working on Industrial and Manufacturing Engineering, Computational Theory and Mathematics and Control and Systems Engineering. According to data from OpenAlex, Tae‐Eog Lee has authored 128 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 99 papers in Industrial and Manufacturing Engineering, 52 papers in Computational Theory and Mathematics and 15 papers in Control and Systems Engineering. Recurrent topics in Tae‐Eog Lee's work include Scheduling and Optimization Algorithms (86 papers), Petri Nets in System Modeling (52 papers) and Manufacturing Process and Optimization (42 papers). Tae‐Eog Lee is often cited by papers focused on Scheduling and Optimization Algorithms (86 papers), Petri Nets in System Modeling (52 papers) and Manufacturing Process and Optimization (42 papers). Tae‐Eog Lee collaborates with scholars based in South Korea, United States and Taiwan. Tae‐Eog Lee's co-authors include Hyun-Jung Kim, Jun-Ho Lee, Ja-Hee Kim, Chihyun Jung, Tae-Sun Yu, Hwan-Yong Lee, Marc E. Posner, Dae-Kyu Kim, Chang Sup Sung and Tae Kyu Kim and has published in prestigious journals such as IEEE Transactions on Automatic Control, European Journal of Operational Research and Operations Research.

In The Last Decade

Tae‐Eog Lee

120 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
Tae‐Eog Lee South Korea 33 2.6k 1.0k 207 174 137 128 2.9k
J.-M. Proth France 18 1.2k 0.5× 529 0.5× 315 1.5× 154 0.9× 102 0.7× 70 1.5k
Arndt Lüder Germany 20 1.2k 0.5× 219 0.2× 232 1.1× 116 0.7× 147 1.1× 160 1.5k
Kleanthis Thramboulidis Greece 21 1.1k 0.4× 480 0.5× 149 0.7× 132 0.8× 199 1.5× 74 1.5k
K. Venkatesh United States 11 563 0.2× 568 0.6× 346 1.7× 60 0.3× 76 0.6× 32 976
Spyros Reveliotis United States 25 1.5k 0.6× 2.0k 2.0× 320 1.5× 381 2.2× 229 1.7× 144 2.6k
Fu-Shiung Hsieh Taiwan 23 773 0.3× 638 0.6× 309 1.5× 124 0.7× 32 0.2× 107 1.3k
Luc Bongaerts Belgium 14 1.3k 0.5× 185 0.2× 218 1.1× 97 0.6× 131 1.0× 30 1.6k
Martin Fabian Sweden 20 825 0.3× 1.4k 1.4× 235 1.1× 310 1.8× 169 1.2× 181 1.8k
Wiesław Kubiak Canada 24 2.0k 0.8× 166 0.2× 198 1.0× 750 4.3× 38 0.3× 96 2.2k
Alois Zoitl Austria 27 2.1k 0.8× 612 0.6× 268 1.3× 228 1.3× 331 2.4× 214 2.6k

Countries citing papers authored by Tae‐Eog Lee

Since Specialization
Citations

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

Fields of papers citing papers by Tae‐Eog Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tae‐Eog Lee. 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 Tae‐Eog Lee. The network helps show where Tae‐Eog Lee may publish in the future.

Co-authorship network of co-authors of Tae‐Eog Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Tae‐Eog Lee. A scholar is included among the top collaborators of Tae‐Eog Lee 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 Tae‐Eog Lee. Tae‐Eog Lee 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.
Kim, Jaewon, et al.. (2023). Practical Reinforcement Learning for Adaptive Photolithography Scheduler in Mass Production. IEEE Transactions on Semiconductor Manufacturing. 37(1). 16–26. 5 indexed citations
2.
Yu, Tae-Sun, et al.. (2022). Cleaning Plan Optimization for Dual-Armed Cluster Tools With General Chamber Cleaning Periods. IEEE Transactions on Automation Science and Engineering. 20(3). 1890–1906. 15 indexed citations
3.
Yu, Tae-Sun, et al.. (2021). Wafer Delay Analysis and Workload Balancing of Parallel Chambers for Dual-Armed Cluster Tools With Multiple Wafer Types. IEEE Transactions on Automation Science and Engineering. 18(3). 1516–1526. 25 indexed citations
4.
Yu, Tae-Sun, et al.. (2021). Feedback Control of Cluster Tools: Stability Against Random Time Disruptions. IEEE Transactions on Automation Science and Engineering. 19(3). 2008–2015. 10 indexed citations
5.
Kim, Woojin, Tae-Sun Yu, & Tae‐Eog Lee. (2020). Integrated Scheduling of a Dual-Armed Cluster Tool for Maximizing Steady Schedule Patterns. IEEE Transactions on Systems Man and Cybernetics Systems. 51(12). 7282–7294. 15 indexed citations
6.
Yu, Tae-Sun, et al.. (2020). Reachability Tree-Based Optimization Algorithm for Cyclic Scheduling of Timed Petri Nets. IEEE Transactions on Automation Science and Engineering. 18(3). 1441–1452. 9 indexed citations
7.
Yu, Tae-Sun, et al.. (2019). Adaptive Scheduling of Cluster Tools With Wafer Delay Constraints and Process Time Variation. IEEE Transactions on Automation Science and Engineering. 17(1). 375–388. 17 indexed citations
8.
Yu, Tae-Sun & Tae‐Eog Lee. (2019). Wafer delay analysis and control of dual-armed cluster tools with chamber cleaning operations. International Journal of Production Research. 58(2). 434–447. 12 indexed citations
9.
Yu, Tae-Sun, et al.. (2018). Scheduling Dual-Armed Cluster Tools for Concurrent Processing of Multiple Wafer Types With Identical Job Flows. IEEE Transactions on Automation Science and Engineering. 16(3). 1058–1070. 18 indexed citations
10.
Kim, Jung‐Hoon, et al.. (2018). Achieving new insights into combat engagement analysis via simulation-based sequential experimentation. 23(4). 51–80. 3 indexed citations
11.
Yu, Tae-Sun, Hyun-Jung Kim, & Tae‐Eog Lee. (2017). Scheduling Single-Armed Cluster Tools With Chamber Cleaning Operations. IEEE Transactions on Automation Science and Engineering. 15(2). 705–716. 44 indexed citations
12.
Yu, Tae-Sun & Tae‐Eog Lee. (2017). Scheduling Dual-Armed Cluster Tools With Chamber Cleaning Operations. IEEE Transactions on Automation Science and Engineering. 16(1). 218–228. 44 indexed citations
13.
Lee, Tae‐Eog, et al.. (2016). Modeling and simulation-based analysis of effectiveness of tactical level chemical defense operations. Winter Simulation Conference. 3098–3109. 1 indexed citations
14.
Yu, Tae-Sun, et al.. (2013). Two-stage lot scheduling with waiting time constraints and due dates. Winter Simulation Conference. 3630–3641. 3 indexed citations
15.
Lee, Tae‐Eog, et al.. (2011). Modeling And Simulation Of Petri Nets For Complex Scheduling Rules Of Automated Manufacturing Systems. Annual Simulation Symposium. 319–324. 4 indexed citations
16.
Lee, Sangjin & Tae‐Eog Lee. (2008). Scheduling a multi-chip package assembly line with reentrant processes and unrelated parallel machines. Winter Simulation Conference. 2286–2291. 4 indexed citations
17.
Lee, Sang‐Jin & Tae‐Eog Lee. (2008). A study for stock allocation problem in the multi-chip package manufacturing. 대한산업공학회 춘계공동학술대회 논문집. 866–871. 1 indexed citations
18.
Lee, Tae‐Eog, et al.. (1996). SEARCH-BASED HEURISTIC ALGORITHMS FOR BASIC PLANNING IN A LARGE SHIPYARD. Journal of Ship Production. 12(4). 211–219. 1 indexed citations
19.
Lee, Tae‐Eog, et al.. (1995). A Review of Korean Shipbuilding Industry and Industrial Engineering Research. IE interfaces. 8(2). 5–20. 1 indexed citations
20.
Lee, Tae‐Eog. (1991). Periodic job shop scheduling /. OhioLink ETD Center (Ohio Library and Information Network). 4 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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