Hsiao-Lan Fang
- Industrial and Manufacturing Engineering top 2%
- Artificial Intelligence top 10%
- Computer Networks and Communications
- Management Science and Operations Research top 10%
- Control and Systems Engineering
- Co-authors
- Peter RossDave CorneDavid CorneShu‐Chuan Chu
- Topics
- Scheduling and Optimization Algorithms (3 papers)Advanced Manufacturing and Logistics Optimization (2 papers)Assembly Line Balancing Optimization (1 paper)
- Cited by
- Industrial and Manufacturing EngineeringArtificial IntelligenceManagement Science and Operations Research
- Journals
- OpenGrey (Institut de l'Information Scientifique et Technique)European Conference on Artificial Intelligence
In The Last Decade
Hsiao-Lan Fang
4 papers receiving 222 citations
Peers
Comparison fields: 5 of 35
- Industrial and Manufacturing Engineering 170
- Artificial Intelligence 112
- Computer Networks and Communications 52
- Management Science and Operations Research 41
- Control and Systems Engineering 30
Countries citing papers authored by Hsiao-Lan Fang
This map shows the geographic impact of Hsiao-Lan Fang'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 Hsiao-Lan Fang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hsiao-Lan Fang more than expected).
Fields of papers citing papers by Hsiao-Lan Fang
This network shows the impact of papers produced by Hsiao-Lan Fang. 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 Hsiao-Lan Fang. The network helps show where Hsiao-Lan Fang may publish in the future.
Co-authorship network of co-authors of Hsiao-Lan Fang
This figure shows the co-authorship network connecting the top 25 collaborators of Hsiao-Lan Fang. A scholar is included among the top collaborators of Hsiao-Lan Fang 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 Hsiao-Lan Fang. Hsiao-Lan Fang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 11 | |
| 3 | A promising hybrid GA/heuristic approach for open-shop scheduling problems | 49 |
| 4 | A Promising Genetic Algorithm Approach to Job-Shop SchedulingRe-Schedulingand Open-Shop Scheduling Problems | 165 |
About Hsiao-Lan Fang
Hsiao-Lan Fang is a scholar working on Industrial and Manufacturing Engineering, Control and Systems Engineering and Management Science and Operations Research, having authored 4 papers that have together received 247 indexed citations. Recurring topics across this work include Scheduling and Optimization Algorithms (3 papers), Advanced Manufacturing and Logistics Optimization (2 papers) and Assembly Line Balancing Optimization (1 paper). The work is most often cited by research in Industrial and Manufacturing Engineering (170 citations), Artificial Intelligence (112 citations) and Management Science and Operations Research (41 citations). Hsiao-Lan Fang has collaborated with scholars based in Australia and Taiwan. Frequent co-authors include Peter Ross, Dave Corne, David Corne and Shu‐Chuan Chu. Their work appears in journals such as OpenGrey (Institut de l'Information Scientifique et Technique) and European Conference on Artificial Intelligence.
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.