Feng-Jang Hwang

705 total citations
45 papers, 503 citations indexed

About

Feng-Jang Hwang is a scholar working on Industrial and Manufacturing Engineering, Building and Construction and Transportation. According to data from OpenAlex, Feng-Jang Hwang has authored 45 papers receiving a total of 503 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Industrial and Manufacturing Engineering, 11 papers in Building and Construction and 8 papers in Transportation. Recurrent topics in Feng-Jang Hwang's work include Scheduling and Optimization Algorithms (14 papers), Advanced Manufacturing and Logistics Optimization (12 papers) and Assembly Line Balancing Optimization (9 papers). Feng-Jang Hwang is often cited by papers focused on Scheduling and Optimization Algorithms (14 papers), Advanced Manufacturing and Logistics Optimization (12 papers) and Assembly Line Balancing Optimization (9 papers). Feng-Jang Hwang collaborates with scholars based in Taiwan, Australia and China. Feng-Jang Hwang's co-authors include Chi‐Hua Chen, Bertrand M.T. Lin, H. T. Kung, Yao‐Huei Huang, Fangying Song, Ling Wu, Hao‐Chun Lu, D. I. Hoult, Mikhail Y. Kovalyov and Amir Salehipour and has published in prestigious journals such as Magnetic Resonance in Medicine, Expert Systems with Applications and IEEE Access.

In The Last Decade

Feng-Jang Hwang

42 papers receiving 482 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Feng-Jang Hwang Taiwan 13 189 85 67 60 50 45 503
Oliviu Matei Romania 11 136 0.7× 109 1.3× 31 0.5× 47 0.8× 20 0.4× 50 371
Francisco Herrera Triguero Spain 10 69 0.4× 200 2.4× 59 0.9× 30 0.5× 41 0.8× 26 380
Tao Ning China 11 251 1.3× 53 0.6× 39 0.6× 41 0.7× 14 0.3× 59 393
Ian Wilson United Kingdom 12 238 1.3× 51 0.6× 17 0.3× 45 0.8× 28 0.6× 31 566
Thomas Bousonville Germany 4 93 0.5× 207 2.4× 34 0.5× 27 0.5× 18 0.4× 9 612
Jácint Szabó Hungary 11 96 0.5× 108 1.3× 71 1.1× 55 0.9× 48 1.0× 46 619
José Luís Santos Portugal 10 122 0.6× 36 0.4× 114 1.7× 34 0.6× 63 1.3× 40 433
Rafael Blanquero Spain 13 66 0.3× 165 1.9× 25 0.4× 30 0.5× 19 0.4× 35 488
Junzi Sun Netherlands 16 89 0.5× 100 1.2× 135 2.0× 28 0.5× 16 0.3× 60 807
Sheng Liu China 13 167 0.9× 299 3.5× 71 1.1× 26 0.4× 14 0.3× 64 583

Countries citing papers authored by Feng-Jang Hwang

Since Specialization
Citations

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

Fields of papers citing papers by Feng-Jang Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Feng-Jang Hwang. 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 Feng-Jang Hwang. The network helps show where Feng-Jang Hwang may publish in the future.

Co-authorship network of co-authors of Feng-Jang Hwang

This figure shows the co-authorship network connecting the top 25 collaborators of Feng-Jang Hwang. A scholar is included among the top collaborators of Feng-Jang Hwang 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 Feng-Jang Hwang. Feng-Jang Hwang 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.
Hwang, Feng-Jang, et al.. (2025). Cluster-Granularity Spatiotemporal Transfer for Cross-Region Graph-Based Traffic Forecasting. IEEE Transactions on Intelligent Transportation Systems. 26(7). 10780–10794.
2.
Hwang, Feng-Jang, et al.. (2024). Dynamic Spatiotemporal Straight-Flow Network for Efficient Learning and Accurate Forecasting in Traffic. IEEE Transactions on Intelligent Transportation Systems. 25(11). 18899–18912. 1 indexed citations
3.
Tsao, Yu‐Chung, et al.. (2024). Intelligent Clinic Nurse Scheduling Considering Nurses Paired with Doctors and Preference of Nurses. Journal of Medical Systems. 48(1). 75–75.
4.
Chen, Chi‐Hua, et al.. (2023). Metro Station functional clustering and dual-view recurrent graph convolutional network for metro passenger flow prediction. Expert Systems with Applications. 247. 122550–122550. 8 indexed citations
5.
Chen, Chi‐Hua, et al.. (2023). Multi-view spatiotemporal learning for traffic forecasting. Information Sciences. 657. 119868–119868. 6 indexed citations
6.
Chen, Chi‐Hua, et al.. (2022). Fast Spatiotemporal Learning Framework for Traffic Flow Forecasting. IEEE Transactions on Intelligent Transportation Systems. 24(8). 8606–8616. 7 indexed citations
7.
Xiong, Lei, et al.. (2021). Environmental Design Strategies to Decrease the Risk of Nosocomial Infection in Medical Buildings Using a Hybrid MCDM Model. Journal of Healthcare Engineering. 2021. 1–17. 11 indexed citations
8.
Fu, Xin, et al.. (2021). Spatial heterogeneity and migration characteristics of traffic congestion—A quantitative identification method based on taxi trajectory data. Physica A Statistical Mechanics and its Applications. 588. 126482–126482. 11 indexed citations
9.
10.
Hwang, Feng-Jang & Yao‐Huei Huang. (2021). An effective logarithmic formulation for piecewise linearization requiring no inequality constraint. Computational Optimization and Applications. 79(3). 601–631. 3 indexed citations
11.
Pan, Mingyang, et al.. (2021). Maritime Target Detection Based on Electronic Image Stabilization Technology of Shipborne Camera. IEICE Transactions on Information and Systems. E104.D(7). 948–960. 4 indexed citations
12.
Pan, Mingyang, et al.. (2020). Lightweight Ship Detection Methods Based on YOLOv3 and DenseNet. Mathematical Problems in Engineering. 2020. 1–10. 24 indexed citations
13.
Tsao, Yu‐Chung, Vo-Van Thanh, & Feng-Jang Hwang. (2020). Energy-efficient single-machine scheduling problem with controllable job processing times under differential electricity pricing. Resources Conservation and Recycling. 161. 104902–104902. 16 indexed citations
14.
Chen, Chi‐Hua, Fangying Song, Feng-Jang Hwang, & Ling Wu. (2019). A probability density function generator based on neural networks. Physica A Statistical Mechanics and its Applications. 541. 123344–123344. 67 indexed citations
15.
Hwang, Feng-Jang & Bertrand M.T. Lin. (2018). Survey and extensions of manufacturing models in two-stage flexible flow shops with dedicated machines. Computers & Operations Research. 98. 103–112. 9 indexed citations
16.
Lin, Bertrand M.T., Feng-Jang Hwang, & Alexander Kononov. (2015). Relocation scheduling subject to fixed processing sequences. Journal of Scheduling. 19(2). 153–163. 7 indexed citations
17.
Hwang, Feng-Jang, Mikhail Y. Kovalyov, & Bertrand M.T. Lin. (2014). Scheduling for fabrication and assembly in a two-machine flowshop with a fixed job sequence. Annals of Operations Research. 217(1). 263–279. 15 indexed citations
18.
Hwang, Feng-Jang, Mikhail Y. Kovalyov, & Bertrand M.T. Lin. (2011). Total completion time minimization in two-machine flow shop scheduling problems with a fixed job sequence. Discrete Optimization. 9(1). 29–39. 11 indexed citations
19.
Hwang, Feng-Jang & Bertrand M.T. Lin. (2011). Coupled-task scheduling on a single machine subject to a fixed-job-sequence. Computers & Industrial Engineering. 60(4). 690–698. 11 indexed citations
20.
Hwang, Feng-Jang & D. I. Hoult. (1998). Automatic probe tuning and matching. Magnetic Resonance in Medicine. 39(2). 214–222. 19 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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