Shu‐Cherng Fang

7.0k total citations
236 papers, 5.1k citations indexed

About

Shu‐Cherng Fang is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Control and Systems Engineering. According to data from OpenAlex, Shu‐Cherng Fang has authored 236 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Computational Theory and Mathematics, 78 papers in Numerical Analysis and 50 papers in Control and Systems Engineering. Recurrent topics in Shu‐Cherng Fang's work include Advanced Optimization Algorithms Research (72 papers), Optimization and Variational Analysis (52 papers) and Optimization and Mathematical Programming (29 papers). Shu‐Cherng Fang is often cited by papers focused on Advanced Optimization Algorithms Research (72 papers), Optimization and Variational Analysis (52 papers) and Optimization and Mathematical Programming (29 papers). Shu‐Cherng Fang collaborates with scholars based in United States, China and Taiwan. Shu‐Cherng Fang's co-authors include Henry L. W. Nuttle, Saowanee Lertworasirikul, Pingke Li, Jeffrey A. Joines, Jian Luo, Guangzhi Li, Y. Tsividis, Elmor L. Peterson, Jay Rajasekera and S. Puthenpura and has published in prestigious journals such as IEEE Transactions on Automatic Control, European Journal of Operational Research and Expert Systems with Applications.

In The Last Decade

Shu‐Cherng Fang

225 papers receiving 4.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shu‐Cherng Fang United States 37 1.7k 1.3k 1.3k 984 740 236 5.1k
Yu‐Chi Ho United States 34 1.4k 0.9× 1.2k 0.9× 847 0.7× 847 0.9× 611 0.8× 121 5.3k
Hervé Lebret France 8 1.2k 0.7× 1.3k 1.0× 616 0.5× 232 0.2× 951 1.3× 14 4.2k
Gilles Savard Canada 29 706 0.4× 1.6k 1.2× 1.5k 1.2× 376 0.4× 614 0.8× 101 4.7k
Arthur M. Geoffrion United States 34 1.5k 0.9× 2.3k 1.7× 1.6k 1.3× 703 0.7× 856 1.2× 63 7.7k
Michael C. Fu United States 41 3.0k 1.8× 727 0.6× 1.1k 0.9× 1.1k 1.1× 290 0.4× 263 6.5k
Thomas L. Magnanti United States 35 974 0.6× 1.4k 1.1× 1.9k 1.4× 645 0.7× 2.0k 2.7× 92 10.9k
Y. C. Ho United States 29 1.2k 0.7× 929 0.7× 817 0.6× 958 1.0× 581 0.8× 120 4.5k
Constantine Caramanis United States 30 1.0k 0.6× 719 0.6× 367 0.3× 615 0.6× 2.0k 2.7× 120 5.2k
Benjamin Van Roy United States 30 1.5k 0.9× 699 0.5× 732 0.6× 2.0k 2.0× 729 1.0× 97 4.9k
Masatoshi Sakawa Japan 40 2.8k 1.7× 2.9k 2.3× 1.4k 1.1× 618 0.6× 342 0.5× 276 5.4k

Countries citing papers authored by Shu‐Cherng Fang

Since Specialization
Citations

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

Fields of papers citing papers by Shu‐Cherng Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shu‐Cherng 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 Shu‐Cherng Fang. The network helps show where Shu‐Cherng Fang may publish in the future.

Co-authorship network of co-authors of Shu‐Cherng Fang

This figure shows the co-authorship network connecting the top 25 collaborators of Shu‐Cherng Fang. A scholar is included among the top collaborators of Shu‐Cherng 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 Shu‐Cherng Fang. Shu‐Cherng Fang 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
1.
2.
Fang, Shu‐Cherng, et al.. (2024). A distributionally robust chance-constrained kernel-free quadratic surface support vector machine. European Journal of Operational Research. 316(1). 46–60. 8 indexed citations
3.
Fang, Shu‐Cherng, et al.. (2024). Enhancing supply chain coordination through transparency initiatives to mitigate product returns. Journal of Retailing and Consumer Services. 78. 103756–103756. 14 indexed citations
4.
Li, Han-Lin, Shu‐Cherng Fang, & Way Kuo. (2024). The Periodic Table of Primes. SSRN Electronic Journal. 1 indexed citations
5.
Yin, Mingqiang, et al.. (2024). Multi-period fourth-party logistics network design with the temporary outsourcing service under demand uncertainty. Computers & Operations Research. 164. 106564–106564. 9 indexed citations
6.
Wang, Ziteng, et al.. (2024). Collaborative supply chain network design under demand uncertainty: A robust optimization approach. International Journal of Production Economics. 279. 109465–109465. 6 indexed citations
7.
Fang, Shu‐Cherng, et al.. (2024). Distributionally robust chance-constrained kernel-based support vector machine. Computers & Operations Research. 170. 106755–106755. 3 indexed citations
8.
Lü, Cheng, Zhibin Deng, Shu‐Cherng Fang, & Wenxun Xing. (2023). A New Global Algorithm for Max-Cut Problem with Chordal Sparsity. Journal of Optimization Theory and Applications. 197(2). 608–638.
9.
Li, Han-Lin, Shu‐Cherng Fang, Bertrand M.T. Lin, & Way Kuo. (2023). Unifying colors by primes. Light Science & Applications. 12(1). 32–32. 7 indexed citations
10.
Fang, Shu‐Cherng, et al.. (2022). A joint model of location, inventory and third-party logistics provider in supply chain network design. Computers & Industrial Engineering. 174. 108809–108809. 14 indexed citations
11.
Wang, Ziteng, Shu‐Cherng Fang, & Wenxun Xing. (2013). On constraint qualifications: Motivation, design and inter-relations. Journal of Industrial and Management Optimization. 9(4). 983–1001. 8 indexed citations
12.
Wang, Yong, Shu‐Cherng Fang, & John E. Lavery. (2006). A compressed primal-dual method for generating bivariate cubic L1 splines. Journal of Computational and Applied Mathematics. 201(1). 69–87. 9 indexed citations
13.
Birbil, Ş. İlker, Shu‐Cherng Fang, J. B. G. Frenk, & Shuzhong Zhang. (2003). Recursive Approximation of the High Dimensional Max Function. Sabanci University. 1 indexed citations
14.
Birbil, Ş. İlker, Shu‐Cherng Fang, Hans Frenk, & Shuzhong Zhang. (2003). Recursive Approximation of the High Dimensional max Function. Data Archiving and Networked Services (DANS). 3 indexed citations
15.
Fang, Shu‐Cherng, Ji Han, & Zhen Huang. (2002). On the Finite Termination of An Entropy Function Based Smoothing Newton Method for Vertical Linear Complementarity Problems. RePub (Erasmus University, Rotterdam). 3 indexed citations
16.
Fang, Shu‐Cherng, et al.. (2002). Entropic perturbation method for solving a system of linear inequalities. Journal of Computational and Applied Mathematics. 145(1). 133–149. 2 indexed citations
17.
Birbil, Ş. İlker, Shu‐Cherng Fang, & Jiye Han. (2002). Entropic Regularization Approach for Mathematical Programs with Equilibrium Constraints. RePub (Erasmus University, Rotterdam). 2 indexed citations
18.
Fang, Shu‐Cherng, et al.. (2002). Solving Variational Inequalities Defined on A Domain with Infinitely Many Linear Constraints. SSRN Electronic Journal. 1 indexed citations
19.
Lertworasirikul, Saowanee, Shu‐Cherng Fang, Jeffrey A. Joines, & Henry L. W. Nuttle. (2002). A Possibility Approach to Fuzzy Data Envelopment Analysis.. 176–179. 7 indexed citations
20.
Tsao, H.-S. Jacob, et al.. (1993). A BAYESIAN INTERPRETATION OF THE LINEARLY-CONSTRAINED CROSS-ENTROPY MINIMIZATION PROBLEM. Engineering Optimization. 22(1). 65–75.

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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