Shih-Ping Han

1.0k citations
13 papers · 688 · 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

11 papers receiving 569 citations

Peers

Shih-Ping Han
Comparison fields: 5 of 84
  • Numerical Analysis 433
  • Computational Theory and Mathematics 396
  • Computational Mechanics 179
  • Control and Systems Engineering 157
  • Computational Mathematics 2
Replace V. N. Malozemov with:
V. N. Malozemov Russia
Willi Hock Germany
Jean-Pierre A. Haeberly United States
Jan-J. Rückmann Germany
E. S. Levitin Germany
Annick Sartenaer Belgium
Clóvis C. Gonzaga Brazil
Roman A. Polyak United States
B. N. Pshenichnyĭ Ukraine
Eskil Hansen Sweden
Shih-Ping Han relative to V. N. Malozemov Russia V. N. Malozemov's profile →
Citations per field
00.5×
V. N. Malozemov · 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

13 of 13 papers shown
#Work
1 1976303
2 1988132
3 198855
4 199253
5 200247
6 199136
7 197735
8 198911
9 20047
10 19793
11 20103
12
Projection algorithms in nonlinear programming
20032
13 19881

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 Computer Graphics and Computer-Aided Design, having authored 13 papers that have together received 688 indexed citations. Recurring topics across this work include Advanced Optimization Algorithms Research (13 papers), Optimization and Variational Analysis (7 papers), Advanced Numerical Analysis Techniques (4 papers), Iterative Methods for Nonlinear Equations (3 papers), Matrix Theory and Algorithms (2 papers), Sparse and Compressive Sensing Techniques (2 papers), Vehicle Routing Optimization Methods (1 paper) and Optimization and Search Problems (1 paper). The work is most often cited by research in Numerical Analysis (433 citations), Computational Theory and Mathematics (396 citations), Computational Mechanics (179 citations), Control and Systems Engineering (157 citations) and Computational Mathematics (2 citations). Shih-Ping Han has collaborated with scholars based in United States and India. Frequent co-authors include Jong‐Shi Pang and Narayan Rangaraj. 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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