Peiping Shen

1.3k total citations
73 papers, 950 citations indexed

About

Peiping Shen is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Control and Systems Engineering. According to data from OpenAlex, Peiping Shen has authored 73 papers receiving a total of 950 indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Numerical Analysis, 57 papers in Computational Theory and Mathematics and 25 papers in Control and Systems Engineering. Recurrent topics in Peiping Shen's work include Advanced Optimization Algorithms Research (63 papers), Optimization and Variational Analysis (41 papers) and Optimization and Mathematical Programming (18 papers). Peiping Shen is often cited by papers focused on Advanced Optimization Algorithms Research (63 papers), Optimization and Variational Analysis (41 papers) and Optimization and Mathematical Programming (18 papers). Peiping Shen collaborates with scholars based in China. Peiping Shen's co-authors include Chunfeng Wang, Hongwei Jiao, Kecun Zhang, Ting Lu, Kaimin Wang, Sanyang Liu, Yanqin Bai, Ya‐Ping Deng, Tongli Zhang and Weimin Li and has published in prestigious journals such as European Journal of Operational Research, Computers & Operations Research and Chaos Solitons & Fractals.

In The Last Decade

Peiping Shen

67 papers receiving 902 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peiping Shen China 20 765 620 387 123 92 73 950
Takahito Kuno Japan 16 529 0.7× 479 0.8× 274 0.7× 35 0.3× 64 0.7× 48 791
Jean‐Louis Goffin Canada 18 571 0.7× 503 0.8× 169 0.4× 76 0.6× 200 2.2× 42 1.1k
Remigijus Paulavičius Lithuania 16 362 0.5× 354 0.6× 103 0.3× 250 2.0× 57 0.6× 48 728
Patrice Marcotte Canada 19 329 0.4× 599 1.0× 368 1.0× 32 0.3× 53 0.6× 44 1.1k
Cihan H. Tuncbilek United States 7 297 0.4× 232 0.4× 162 0.4× 37 0.3× 42 0.5× 7 553
Welington de Oliveira France 16 343 0.4× 301 0.5× 113 0.3× 72 0.6× 186 2.0× 46 709
Deren Han China 19 388 0.5× 487 0.8× 210 0.5× 21 0.2× 213 2.3× 64 1.1k
J. G. Ecker United States 16 410 0.5× 399 0.6× 442 1.1× 27 0.2× 39 0.4× 40 872
Jordi Castro Spain 14 193 0.3× 193 0.3× 84 0.2× 98 0.8× 68 0.7× 52 543
Claudio Gentile Italy 15 232 0.3× 206 0.3× 131 0.3× 143 1.2× 108 1.2× 45 885

Countries citing papers authored by Peiping Shen

Since Specialization
Citations

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

Fields of papers citing papers by Peiping Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peiping Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Peiping Shen. A scholar is included among the top collaborators of Peiping Shen 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 Peiping Shen. Peiping Shen 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.
Deng, Ya‐Ping & Peiping Shen. (2025). A new branch-and-bound algorithm for generalized affine multiplicative programming. Journal of Global Optimization. 93(1). 87–112.
2.
Shen, Peiping, et al.. (2024). An efficient branch and bound reduction algorithm for globally solving linear fractional programming problems. Chaos Solitons & Fractals. 182. 114757–114757. 2 indexed citations
3.
Zhang, Yanzhen, et al.. (2024). An efficient branch-and-bound algorithm using an adaptive branching rule with quadratic convex relaxation for globally solving general linear multiplicative programs. Journal of Computational and Applied Mathematics. 450. 116035–116035. 5 indexed citations
4.
Shen, Peiping, et al.. (2024). A one-dimensional branching rule based branch-and-bound algorithm for minimax linear fractional programming. Journal of Computational and Applied Mathematics. 448. 115900–115900. 1 indexed citations
5.
Shen, Peiping, et al.. (2023). An efficient spatial branch-and-bound algorithm using an adaptive branching rule for linear multiplicative programming. Journal of Computational and Applied Mathematics. 426. 115100–115100. 14 indexed citations
6.
Shen, Peiping, et al.. (2023). Globally minimizing a class of linear multiplicative forms via simplicial branch-and-bound. Journal of Global Optimization. 86(2). 303–321. 7 indexed citations
7.
Jiao, Hongwei, et al.. (2023). Efficient algorithm for globally computing the min–max linear fractional programming problem. RAIRO. Operations research. 57(3). 1523–1537. 4 indexed citations
8.
Jiao, Hongwei, et al.. (2022). Effective algorithm and computational complexity for solving sum of linear ratios problem. Journal of Industrial and Management Optimization. 19(6). 4410–4427. 13 indexed citations
9.
Shen, Peiping, Kaimin Wang, & Ting Lu. (2020). Outer space branch and bound algorithm for solving linear multiplicative programming problems. Journal of Global Optimization. 78(3). 453–482. 23 indexed citations
10.
Shen, Peiping, et al.. (2019). A practicable contraction approach for the sum of the generalized polynomial ratios problem. European Journal of Operational Research. 278(1). 36–48. 9 indexed citations
11.
12.
Shen, Peiping & Ting Lu. (2018). Regional division and reduction algorithm for minimizing the sum of linear fractional functions. Journal of Inequalities and Applications. 2018(1). 63–63. 22 indexed citations
13.
Shen, Peiping, et al.. (2018). Range division and linearization algorithm for a class of linear ratios optimization problems. Journal of Computational and Applied Mathematics. 350. 324–342. 46 indexed citations
14.
Shen, Peiping & Chunfeng Wang. (2017). Linear decomposition approach for a class of nonconvex programming problems. Journal of Inequalities and Applications. 2017(1). 74–74. 19 indexed citations
15.
Liu, Jian & Peiping Shen. (2011). Accelerating Branch and Bound Algorithm for Sum of Quadratic Ratios Problem. Acta Mathematicae Applicatae Sinica English Series. 1 indexed citations
16.
Wang, Chunfeng, Sanyang Liu, & Peiping Shen. (2011). Global minimization of a generalized linear multiplicative programming. Applied Mathematical Modelling. 36(6). 2446–2451. 35 indexed citations
17.
Shen, Peiping. (2010). An Efficient Algorithm of Global Optimization for Sum of Quadratic Ratios Problem with Nonconvex Quadratic Constraints. Mathematica Applicata. 1 indexed citations
18.
Shen, Peiping, et al.. (2008). A nonisolated optimal solution for special reverse convex programming problems. Journal of Computational and Applied Mathematics. 224(1). 219–229. 3 indexed citations
19.
Shen, Peiping, et al.. (2007). Accelerating method of global optimization for signomial geometric programming. Journal of Computational and Applied Mathematics. 214(1). 66–77. 13 indexed citations
20.
Shen, Peiping, et al.. (2006). Optimization of Land Use Structure and Efficient Land Use in Desert Regions at Ecological Security Level——A Case Study in the Horqin Sandland. Arid Zone Research. 1 indexed citations

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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