Shih-Ping Han

1.0k citations
17 papers · 796 · h-index 8

Impact in

    • Advanced Optimization Algorithms Research
    • Iterative Methods for Nonlinear Equations
    • Optimization and Variational Analysis
    • Matrix Theory and Algorithms
    • Advanced Multi-Objective Optimization Algorithms

Papers in

Shih-Ping Han

14 papers receiving 654 citations

Peers

Shih-Ping Han
Comparison fields: 5 of 93
  • Numerical Analysis 501
  • Computational Theory and Mathematics 450
  • Computational Mechanics 187
  • Control and Systems Engineering 203
  • Management Science and Operations Research 47
Replace Rembert Reemtsen with:
Rembert Reemtsen Germany
V. N. Malozemov Russia
E. S. Levitin Russia
Roman G. Strongin Russia
Eskil Hansen Sweden
Jan-J. Rückmann Germany
B. N. Pshenichnyĭ Ukraine
J. E. Dennis United States
Annick Sartenaer Belgium
Yu. G. Evtushenko Russia
Shih-Ping Han relative to Rembert Reemtsen Germany Rembert Reemtsen's profile →
Citations per field
00.5×1.5×1.8×
Rembert Reemtsen · 1×
Citations per year

Countries citing papers authored by Shih-Ping Han

Since Specialization
Citations

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

Fields of papers citing papers by Shih-Ping Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shih-Ping Han. 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 Shih-Ping Han. The network helps show where Shih-Ping Han may publish in the future.

Co-authors

The 2 scholars most cited alongside Shih-Ping Han, 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 Shih-Ping Han Line = papers co-authored together Shih-Ping Han links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 1976371
2 1988140
3 199260
4 198856
5 200248
6 197741
7 199139
8 198912
9 20047
10 20106
11 19786
12 19793
13 19882
14
Projection algorithms in nonlinear programming
20032
15 19812
16 20121
17 19760

About Shih-Ping Han

Shih-Ping Han is a scholar working on Numerical Analysis, Computational Theory and Mathematics, Computational Mechanics, Computer Networks and Communications and Industrial and Manufacturing Engineering, having authored 17 papers that have together received 796 indexed citations. Recurring topics across this work include Advanced Optimization Algorithms Research (16 papers), Optimization and Variational Analysis (9 papers), Advanced Numerical Analysis Techniques (4 papers), Iterative Methods for Nonlinear Equations (3 papers), Sparse and Compressive Sensing Techniques (3 papers), Vehicle Routing Optimization Methods (2 papers), Matrix Theory and Algorithms (2 papers) and Optimization and Search Problems (2 papers). The work is most often cited by research in Numerical Analysis (501 citations), Computational Theory and Mathematics (450 citations), Computational Mechanics (187 citations), Control and Systems Engineering (203 citations) and Management Science and Operations Research (47 citations). Shih-Ping Han has collaborated with scholars based in United States and India. Frequent co-authors include Narayan Rangaraj and Jong‐Shi Pang. Their work appears in journals such as Mathematics of Operations Research, SIAM Journal on Optimization, Mathematical Programming, SIAM Journal on Control and Optimization and Numerische Mathematik.

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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