Langchun Si

568 citations
8 papers · 390 · 1 hit paper · h-index 6

Impact in

Papers in

Langchun Si

8 papers receiving 385 citations

Langchun Si's Hit Papers

Evolutionary Large-Scale Multi-Objective Optimization: A Survey 2021 · 276 citations
2760+1+3Years since publication50100150200250

Peers

Langchun Si
Comparison fields: 5 of 59
  • Computational Theory and Mathematics 228
  • Artificial Intelligence 246
  • Industrial and Manufacturing Engineering 39
  • Management Science and Operations Research 31
  • Computational Mathematics 1
Replace Maciej Smółka with:
Maciej Smółka Poland
Zefeng Chen China
Borhan Kazimipour Australia
Ulrike Baumgartner Austria
Yoel Tenne Israel
Martin Zaefferer Germany
Y. Yang China
Jiajie Mo China
Jiawei Yuan China
Yuanchao Liu China
Langchun Si relative to Maciej Smółka Poland Maciej Smółka's profile →
Citations per field
00.5×10×20×32.7×
Maciej Smółka · 1×
Citations per year

Countries citing papers authored by Langchun Si

Since Specialization
Citations

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

Fields of papers citing papers by Langchun Si

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Langchun Si. 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 Langchun Si. The network helps show where Langchun Si may publish in the future.

Co-authors

The 17 scholars most cited alongside Langchun Si, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Langchun Si Line = papers co-authored together Langchun Si links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1
Evolutionary Large-Scale Multi-Objective Optimization: A Survey
Hit paper breakdown →
2021276
2 202251
3 202325
4 201924
5 20226
6 20255
7 20232
8 20251

About Langchun Si

Langchun Si is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Radiation, Pulmonary and Respiratory Medicine and Civil and Structural Engineering, having authored 8 papers that have together received 390 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (6 papers), Metaheuristic Optimization Algorithms Research (4 papers), Advanced Radiotherapy Techniques (3 papers), Evolutionary Algorithms and Applications (3 papers), Radiation Therapy and Dosimetry (2 papers), Hepatocellular Carcinoma Treatment and Prognosis (1 paper), Seismology and Earthquake Studies (1 paper) and Earthquake Detection and Analysis (1 paper). The work is most often cited by research in Computational Theory and Mathematics (228 citations), Artificial Intelligence (246 citations), Industrial and Manufacturing Engineering (39 citations), Management Science and Operations Research (31 citations) and Computational Mathematics (1 citation). Langchun Si has collaborated with scholars based in China, Germany and Hong Kong. Frequent co-authors include Ye Tian, Xingyi Zhang, Yaochu Jin, Kay Chen Tan, Cheng He, Ran Cheng, Yuanzhi Hu, Jianfeng Qiu, Shangshang Yang and Lei Zhang. Their work appears in journals such as IEEE Transactions on Emerging Topics in Computational Intelligence, Complex & Intelligent Systems, IEEE Transactions on Evolutionary Computation, ACM Computing Surveys and IEEE Transactions on Systems Man and Cybernetics Systems.

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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