Xiwen Cai

1.4k total citations
34 papers, 1.1k citations indexed

About

Xiwen Cai is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Xiwen Cai has authored 34 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computational Theory and Mathematics, 20 papers in Artificial Intelligence and 10 papers in Statistics, Probability and Uncertainty. Recurrent topics in Xiwen Cai's work include Advanced Multi-Objective Optimization Algorithms (30 papers), Metaheuristic Optimization Algorithms Research (20 papers) and Evolutionary Algorithms and Applications (14 papers). Xiwen Cai is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (30 papers), Metaheuristic Optimization Algorithms Research (20 papers) and Evolutionary Algorithms and Applications (14 papers). Xiwen Cai collaborates with scholars based in China, United Kingdom and Australia. Xiwen Cai's co-authors include Liang Gao, Haobo Qiu, Xinyu Li, Fan Li, Chen Jiang, Xinyu Shao, Weiming Shen, Liming Chen, Fan Li and Peigen Li and has published in prestigious journals such as AIAA Journal, Information Sciences and IEEE Transactions on Antennas and Propagation.

In The Last Decade

Xiwen Cai

30 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiwen Cai China 19 784 600 263 200 137 34 1.1k
Zan Yang China 19 534 0.7× 334 0.6× 445 1.7× 206 1.0× 226 1.6× 112 1.2k
Songqing Shan Canada 12 826 1.1× 251 0.4× 535 2.0× 274 1.4× 215 1.6× 16 1.2k
Michael J. Sasena United States 10 593 0.8× 198 0.3× 273 1.0× 307 1.5× 65 0.5× 12 937
D. Huang United States 3 517 0.7× 216 0.4× 257 1.0× 307 1.5× 51 0.4× 3 734
Jan Griebsch Germany 6 410 0.5× 132 0.2× 257 1.0× 206 1.0× 140 1.0× 8 824
Tobias Wagner Germany 12 428 0.5× 305 0.5× 126 0.5× 183 0.9× 33 0.2× 31 657
Mohsen Rashki Iran 19 372 0.5× 242 0.4× 648 2.5× 99 0.5× 525 3.8× 46 1.3k
Majid Ilchi Ghazaan Iran 18 492 0.6× 387 0.6× 114 0.4× 45 0.2× 668 4.9× 32 1.1k
Gregorio Toscano‐Pulido Mexico 14 508 0.6× 428 0.7× 51 0.2× 92 0.5× 36 0.3× 41 718
Saúl Zapotecas–Martínez Mexico 16 611 0.8× 551 0.9× 35 0.1× 118 0.6× 77 0.6× 52 827

Countries citing papers authored by Xiwen Cai

Since Specialization
Citations

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

Fields of papers citing papers by Xiwen Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiwen Cai

This figure shows the co-authorship network connecting the top 25 collaborators of Xiwen Cai. A scholar is included among the top collaborators of Xiwen Cai 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 Xiwen Cai. Xiwen Cai 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.
Cai, Xiwen, Han Chen, Yongfeng Zheng, & Liang Gao. (2025). Efficient Bayesian optimization for cheap and expensive multi-objective problems. Applied Mathematical Modelling. 151. 116501–116501.
3.
Lu, Hongbing, Zan Wei Yang, Jihui Huang, Liming Chen, & Xiwen Cai. (2025). Angle information enhanced kriging-assisted adaptive evolutionary algorithm for computationally highly expensive high-dimensional problems. Swarm and Evolutionary Computation. 96. 101992–101992.
4.
Cai, Xiwen, Tao Zou, & Liang Gao. (2023). Surrogate-assisted operator-repeated evolutionary algorithm for computationally expensive multi-objective problems. Applied Soft Computing. 147. 110785–110785. 4 indexed citations
5.
Zheng, Yongfeng, Jianhua Xiang, Ping Li, et al.. (2023). Hierarchical topology optimization with varying micro-structural aspect ratios. Engineering Analysis with Boundary Elements. 156. 34–47. 5 indexed citations
6.
Cai, Xiwen, Gan Ruan, Bo Yuan, & Liang Gao. (2023). Complementary surrogate-assisted differential evolution algorithm for expensive multi-objective problems under a limited computational budget. Information Sciences. 632. 791–814. 11 indexed citations
7.
Yang, Zan, Haobo Qiu, Liang Gao, Liming Chen, & Xiwen Cai. (2023). Constraint boundary pursuing-based surrogate-assisted differential evolution for expensive optimization problems with mixed constraints. Structural and Multidisciplinary Optimization. 66(2). 18 indexed citations
8.
Li, Fan, Liang Gao, Weiming Shen, Xiwen Cai, & Shifeng Huang. (2020). A Surrogate-Assisted Offspring Generation Method for Expensive Multi-objective optimization Problems. 1–8. 8 indexed citations
9.
Li, Fan, Xiwen Cai, Liang Gao, & Weiming Shen. (2020). A Surrogate-Assisted Multiswarm Optimization Algorithm for High-Dimensional Computationally Expensive Problems. IEEE Transactions on Cybernetics. 51(3). 1390–1402. 129 indexed citations
10.
Yang, Zan, Haobo Qiu, Liang Gao, et al.. (2019). Surrogate-assisted classification-collaboration differential evolution for expensive constrained optimization problems. Information Sciences. 508. 50–63. 63 indexed citations
11.
Cai, Xiwen, Liang Gao, & Xinyu Li. (2019). Efficient Generalized Surrogate-Assisted Evolutionary Algorithm for High-Dimensional Expensive Problems. IEEE Transactions on Evolutionary Computation. 24(2). 365–379. 127 indexed citations
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Cai, Xiwen, Liang Gao, & Fan Li. (2019). Sequential approximation optimization assisted particle swarm optimization for expensive problems. Applied Soft Computing. 83. 105659–105659. 30 indexed citations
15.
Cai, Xiwen, Haobo Qiu, Liang Gao, Xiaoke Li, & Xinyu Shao. (2018). A hybrid global optimization method based on multiple metamodels. Engineering Computations. 35(1). 71–90. 4 indexed citations
16.
Li, Fan, Xiwen Cai, & Liang Gao. (2018). Ensemble of surrogates assisted particle swarm optimization of medium scale expensive problems. Applied Soft Computing. 74. 291–305. 64 indexed citations
17.
Cai, Xiwen, Haobo Qiu, Liang Gao, Wei Li, & Xinyu Shao. (2017). Adaptive Radial-Basis-Function-Based Multifidelity Metamodeling for Expensive Black-Box Problems. AIAA Journal. 55(7). 2424–2436. 40 indexed citations
18.
Cai, Xiwen, Haobo Qiu, Liang Gao, & Xinyu Shao. (2017). Metamodeling for high dimensional design problems by multi-fidelity simulations. Structural and Multidisciplinary Optimization. 56(1). 151–166. 58 indexed citations
19.
Chen, Liming, Haobo Qiu, Chen Jiang, Xiwen Cai, & Liang Gao. (2017). Ensemble of surrogates with hybrid method using global and local measures for engineering design. Structural and Multidisciplinary Optimization. 57(4). 1711–1729. 31 indexed citations
20.
Cai, Xiwen, Haobo Qiu, Liang Gao, Peng Yang, & Xinyu Shao. (2015). An enhanced RBF-HDMR integrated with an adaptive sampling method for approximating high dimensional problems in engineering design. Structural and Multidisciplinary Optimization. 53(6). 1209–1229. 49 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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