Lixin Tang

9.0k total citations
339 papers, 6.8k citations indexed

About

Lixin Tang is a scholar working on Industrial and Manufacturing Engineering, Control and Systems Engineering and Artificial Intelligence. According to data from OpenAlex, Lixin Tang has authored 339 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 207 papers in Industrial and Manufacturing Engineering, 71 papers in Control and Systems Engineering and 52 papers in Artificial Intelligence. Recurrent topics in Lixin Tang's work include Scheduling and Optimization Algorithms (139 papers), Advanced Manufacturing and Logistics Optimization (108 papers) and Optimization and Packing Problems (77 papers). Lixin Tang is often cited by papers focused on Scheduling and Optimization Algorithms (139 papers), Advanced Manufacturing and Logistics Optimization (108 papers) and Optimization and Packing Problems (77 papers). Lixin Tang collaborates with scholars based in China, United Kingdom and United States. Lixin Tang's co-authors include Jiyin Liu, Xianpeng Wang, Aiying Rong, Zihou Yang, Yun Dong, Ying Meng, Gongshu Wang, Hua Gong, Haichao Fan and Yue Zhao and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Cleaner Production.

In The Last Decade

Lixin Tang

308 papers receiving 6.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lixin Tang China	43	3.9k	1.3k	1.1k	827	564	339	6.8k
Runwei Cheng Japan	18	2.7k 0.7×	1.2k 1.0×	1.0k 0.9×	703 0.9×	558 1.0×	31	6.1k
Cheng Wu China	38	1.7k 0.4×	2.0k 1.5×	789 0.7×	406 0.5×	719 1.3×	291	5.4k
David W. Coit United States	52	1.2k 0.3×	966 0.7×	1.6k 1.4×	1.0k 1.2×	597 1.1×	201	12.0k
Olivier de Weck United States	40	1.2k 0.3×	589 0.5×	1.4k 1.3×	675 0.8×	683 1.2×	375	7.5k
T. Warren Liao United States	41	1.4k 0.3×	1.6k 1.3×	372 0.3×	345 0.4×	370 0.7×	142	6.4k
Duncan McFarlane United Kingdom	36	2.0k 0.5×	371 0.3×	2.0k 1.8×	234 0.3×	471 0.8×	184	6.0k
Nenad Mladenović Serbia	43	7.2k 1.8×	2.6k 2.0×	1.0k 0.9×	1.2k 1.5×	1.3k 2.4×	246	11.1k
Yi Mei New Zealand	40	2.3k 0.6×	3.1k 2.4×	503 0.5×	1.6k 2.0×	809 1.4×	250	6.1k
Jean‐Yves Potvin Canada	45	6.9k 1.8×	2.2k 1.7×	740 0.7×	922 1.1×	976 1.7×	117	10.2k
Pei‐Chann Chang Taiwan	49	2.0k 0.5×	2.0k 1.5×	506 0.5×	408 0.5×	364 0.6×	200	6.2k

Countries citing papers authored by Lixin Tang

Since Specialization

Citations

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

Fields of papers citing papers by Lixin Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lixin Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Lixin Tang. A scholar is included among the top collaborators of Lixin Tang 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 Lixin Tang. Lixin Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Wang, Kun, et al.. (2025). CO reduction in sintering flue gas by CFD-ML for process parameters optimization. Journal of Cleaner Production. 500. 145268–145268.

Wu, Wei, Yapeng Liu, Lixin Tang, et al.. (2025). SBDNet: A Scale and Edge Guided Bidecoding Network for Land Parcel Extraction. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 8057–8070. 1 indexed citations

Chang, Miao, Shengnan Zhao, Lixin Tang, Jiyin Liu, & Yanyan Zhang. (2024). A reinforcement learning based Lagrangian relaxation algorithm for multi-energy allocation problem in steel enterprise. Computers & Chemical Engineering. 194. 108948–108948. 1 indexed citations

Tang, Lixin, et al.. (2024). NSMD-NAS: Retinal Image Segmentation with Neural Architecture Search and Non-Subsampled Multiscale Decomposition. 1–8.

Tang, Lixin, et al.. (2024). Bi-objective approach for lot-sizing problem in cold rolling production planning. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 99–100.

Tang, Lixin, et al.. (2024). An Enhanced Surrogate-Assisted Multi-Objective Differential Evolution Algorithm with Self-Adaptive Strategies for Order Planning in Hot Rolling Process. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 643–646.

Bernal, David E., et al.. (2023). Modeling for integrated refinery planning with crude-oil scheduling. Process Safety and Environmental Protection. 192. 141–157. 7 indexed citations

Tang, Lixin, et al.. (2023). Experiments and evaluation on residual strength of X52 steel pipe with various internal defects. Frontiers in Energy Research. 10. 1 indexed citations

Tang, Lixin, et al.. (2019). Global Method for a Class of Operation Optimization Problem in Steel Rolling Systems. Industrial & Engineering Chemistry Research. 58(14). 5552–5566. 1 indexed citations

10.

Tang, Lixin, et al.. (2015). Analysis and Evaluation of Relative Efficiency of Warehousing and Distribution Operations Based on Mixed DEA Model. SHILAP Revista de lepidopterología. 3 indexed citations

11.

Tang, Lixin. (2012). Improved data-driven subspace algorithm for energy prediction in iron and steel industry. Control theory & applications. 2 indexed citations

12.

Dai, Meifeng & Lixin Tang. (2012). The pointwise densities of 3‐part Cantor measure. Mathematical Methods in the Applied Sciences. 35(17). 2000–2016.

13.

Tang, Lixin. (2012). Stochastic Optimization Scheduling Method for Hydrothermal Power Systems With Stochastic Loads. Proceedings of the CSEE. 5 indexed citations

14.

Tang, Lixin. (2011). Multi-objective Stochastic Scheduling Models for Hydrothermal Plants Based on Fuzzy Chance Constrained Programming. Proceedings of the CSEE. 1 indexed citations

15.

Luo, Zhihong & Lixin Tang. (2011). Modeling and solution to integrated production and logistics planning of steel making and hot rolling. Guanli kexue xuebao. 14(6). 16–23. 1 indexed citations

16.

Tang, Lixin. (2009). Study on Agricultural Insurance Based on Products Marketing. Modern Applied Science. 3(7). 2 indexed citations

17.

Tang, Lixin, et al.. (2006). Dynasearch algorithms for single machine scheduling problem with total weighted satisfaction. Guanli kexue xuebao. 1 indexed citations

18.

Li, Jianxiang & Lixin Tang. (2005). Model and algorithm for hot rolling steel tube MPS. Journal of systems engineering. 1 indexed citations

19.

Tang, Lixin. (2005). A Model with Regularity for Open Pit Mine Short Term Production Scheduling. Systems Engineering - Theory & Practice.

20.

Tang, Lixin. (2004). Combine Column Generation with GUB to Solve the Steel-Iron Raw Materials Purchasing Lot-Sizing Problem. Acta Automatica Sinica. 4 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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