Qiang Long

437 total citations
21 papers, 337 citations indexed

About

Qiang Long is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Numerical Analysis. According to data from OpenAlex, Qiang Long has authored 21 papers receiving a total of 337 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Theory and Mathematics, 10 papers in Artificial Intelligence and 9 papers in Numerical Analysis. Recurrent topics in Qiang Long's work include Advanced Optimization Algorithms Research (9 papers), Advanced Multi-Objective Optimization Algorithms (7 papers) and Metaheuristic Optimization Algorithms Research (6 papers). Qiang Long is often cited by papers focused on Advanced Optimization Algorithms Research (9 papers), Advanced Multi-Objective Optimization Algorithms (7 papers) and Metaheuristic Optimization Algorithms Research (6 papers). Qiang Long collaborates with scholars based in China, Australia and South Korea. Qiang Long's co-authors include Changzhi Wu, Xiangyu Wang, Jueyou Li, Tingwen Huang, Zhiyou Wu, Xue Wu, Kris M. Y. Law, Yi Tan, Junxiang Zhu and Yongze Song and has published in prestigious journals such as Expert Systems with Applications, Automation in Construction and Applied Mathematics and Computation.

In The Last Decade

Qiang Long

19 papers receiving 321 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qiang Long China	11	101	81	54	47	40	21	337
Dang-Hai Pham Vietnam	4	84 0.8×	39 0.5×	37 0.7×	19 0.4×	56 1.4×	6	316
Sujin Kim South Korea	11	74 0.7×	72 0.9×	24 0.4×	17 0.4×	48 1.2×	23	349
Yancang Li China	10	203 2.0×	81 1.0×	38 0.7×	33 0.7×	90 2.3×	51	473
Nikos Ath. Kallioras Greece	10	123 1.2×	101 1.2×	17 0.3×	56 1.2×	28 0.7×	17	378
Saideep Nannapaneni United States	12	49 0.5×	71 0.9×	23 0.4×	32 0.7×	19 0.5×	40	404
Ataollah Zaerreza Iran	11	106 1.0×	122 1.5×	23 0.4×	28 0.6×	24 0.6×	16	321
Saman M. Almufti‎ Iraq	12	176 1.7×	49 0.6×	46 0.9×	21 0.4×	46 1.1×	53	561
Changsheng Zhang China	11	96 1.0×	19 0.2×	54 1.0×	46 1.0×	87 2.2×	61	419
Blas Galván Spain	9	57 0.6×	89 1.1×	12 0.2×	23 0.5×	25 0.6×	24	381

Countries citing papers authored by Qiang Long

Since Specialization

Citations

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

Fields of papers citing papers by Qiang Long

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiang Long

This figure shows the co-authorship network connecting the top 25 collaborators of Qiang Long. A scholar is included among the top collaborators of Qiang Long 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 Qiang Long. Qiang Long 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

Long, Qiang, et al.. (2023). Shortest Path Problem for Resource-Constrained Project Scheduling Based on Deep Reinforcement Learning. 91–97. 1 indexed citations

Long, Qiang, et al.. (2022). Multi-objective stochastic project scheduling with alternative execution methods: An improved quantum-behaved particle swarm optimization approach. Expert Systems with Applications. 203. 117029–117029. 21 indexed citations

Long, Qiang, et al.. (2022). Methods and Applications of Clusterwise Linear Regression: A Survey and Comparison. ACM Transactions on Knowledge Discovery from Data. 17(3). 1–54. 7 indexed citations

Long, Qiang, et al.. (2022). Path planning algorithm for sweeping robot full traversal cleaning area. 127–132.

Long, Qiang, et al.. (2021). A novel solver for multi-objective optimization: dynamic non-dominated sorting genetic algorithm (DNSGA). Soft Computing. 26(2). 725–747. 11 indexed citations

Long, Qiang, Xue Wu, & Changzhi Wu. (2020). Non-dominated sorting methods for multi-objective optimization: Review and numerical comparison. Journal of Industrial and Management Optimization. 17(2). 1001–1023. 26 indexed citations

Tan, Yi, Yongze Song, Junxiang Zhu, et al.. (2018). Optimizing lift operations and vessel transport schedules for disassembly of multiple offshore platforms using BIM and GIS. Automation in Construction. 94. 328–339. 26 indexed citations

Long, Qiang, Changzhi Wu, Xiangyu Wang, & Zhiyou Wu. (2017). A modified quasisecant method for global optimization. Applied Mathematical Modelling. 51. 21–37. 3 indexed citations

Long, Qiang & Changzhi Wu. (2017). A nonsmooth equation system solver based on subgradient method. eSpace (Curtin University). 1–5.

10.

Long, Qiang, et al.. (2015). A Multiobjective Genetic Algorithm Based on a Discrete Selection Procedure. Mathematical Problems in Engineering. 2015. 1–17. 18 indexed citations

11.

Li, Jueyou, Changzhi Wu, Zhiyou Wu, Qiang Long, & Xiangyu Wang. (2015). Distributed proximal-gradient method for convex optimization with inequality constraints. ANZIAM Journal. 56. 160–160. 1 indexed citations

12.

Li, Jueyou, Zhiyou Wu, Changzhi Wu, Qiang Long, & Xiangyu Wang. (2015). An Inexact Dual Fast Gradient-Projection Method for Separable Convex Optimization with Linear Coupled Constraints. Journal of Optimization Theory and Applications. 168(1). 153–171. 16 indexed citations

13.

Long, Qiang, Changzhi Wu, Tingwen Huang, & Xiangyu Wang. (2015). A genetic algorithm for unconstrained multi-objective optimization. Swarm and Evolutionary Computation. 22. 1–14. 63 indexed citations

14.

Li, Jueyou, Changzhi Wu, Zhiyou Wu, Qiang Long, & Xiangyu Wang. (2014). DISTRIBUTED PROXIMAL-GRADIENT METHOD FOR CONVEX OPTIMIZATION WITH INEQUALITY CONSTRAINTS. The ANZIAM Journal. 56(2). 160–178. 4 indexed citations

15.

Li, Jueyou, Changzhi Wu, Zhiyou Wu, & Qiang Long. (2014). Gradient-free method for nonsmooth distributed optimization. Journal of Global Optimization. 61(2). 325–340. 35 indexed citations

16.

Long, Qiang, Changzhi Wu, & Xiangyu Wang. (2014). A system of nonsmooth equations solver based upon subgradient method. Applied Mathematics and Computation. 251. 284–299. 41 indexed citations

17.

Long, Qiang & Changzhi Wu. (2014). A hybrid method combining genetic algorithm andHooke-Jeeves method for constrained global optimization. Journal of Industrial and Management Optimization. 10(4). 1279–1296. 43 indexed citations

18.

Long, Qiang & Changzhi Wu. (2013). A quasisecant method for solving a system of nonsmooth equations. Computers & Mathematics with Applications. 66(4). 419–431. 2 indexed citations

19.

Wu, Changzhi, Chaojie Li, & Qiang Long. (2013). A DC programming approach for sensor network localization with uncertainties in anchor positions. Journal of Industrial and Management Optimization. 10(3). 817–826. 10 indexed citations

20.

Long, Qiang. (2010). A global optimized solution of nonlinear programming with equality constraints. 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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