Ching-Fang Liaw

24 papers receiving 645 citations

Peers

Ching-Fang Liaw
Comparison fields: 5 of 55
  • Industrial and Manufacturing Engineering 555
  • Computer Networks and Communications 153
  • Artificial Intelligence 125
  • Management Science and Operations Research 80
  • Management Information Systems 51
Replace Moshe B. Rosenwein with:
Moshe B. Rosenwein United States
Marjan van den Akker Netherlands
Kerem Bülbül Türkiye
Francis J. Vasko United States
Deniz Türsel Eliiyi Türkiye
Francisco Ángel-Bello Mexico
Ada Álvarez Mexico
Greger Ottosson United States
Saïd Hanafi France
Nikolay Tchernev France
Ching-Fang Liaw relative to Moshe B. Rosenwein United States Moshe B. Rosenwein's profile →
Citations per field
00.5×2.8×
Moshe B. Rosenwein · 1×
Citations per year

Countries citing papers authored by Ching-Fang Liaw

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Fang Liaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Fang Liaw. 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 Ching-Fang Liaw. The network helps show where Ching-Fang Liaw may publish in the future.

Co-authorship network of co-authors of Ching-Fang Liaw

This figure shows the co-authorship network connecting the top 25 collaborators of Ching-Fang Liaw. A scholar is included among the top collaborators of Ching-Fang Liaw 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 Ching-Fang Liaw. Ching-Fang Liaw 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
#WorkIndexed citations
1 42
2 17
3 0
4 5
5 2
6 1
7 17
8 11
9 29
10 15
11 11
12 1
13 55
14
1
15 35
16 27
17 48
18 3
19
Heuristic search and its transit applications.
0
20 10

About Ching-Fang Liaw

Ching-Fang Liaw is a scholar working on Industrial and Manufacturing Engineering, Computer Networks and Communications and Software, having authored 26 papers that have together received 685 indexed citations. Recurring topics across this work include Scheduling and Optimization Algorithms (18 papers), Advanced Manufacturing and Logistics Optimization (12 papers) and Assembly Line Balancing Optimization (8 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (555 citations), Computer Networks and Communications (153 citations) and Management Science and Operations Research (80 citations). Ching-Fang Liaw has collaborated with scholars based in Taiwan, United States and Türkiye. Frequent co-authors include Yang-Kuei Lin, Chelsea C. White, Huai-Wei Lo, Muhammet Gül, Mingchih Chen, Dinesh Chandra Agrawal, Rung-Ching Chen and Tao-Ming Cheng. Their work appears in journals such as European Journal of Operational Research, Computers & Operations Research and Computers & Industrial Engineering.

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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