Yutao Qi

2.7k total citations · 2 hit papers
55 papers, 2.0k citations indexed

About

Yutao Qi is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Civil and Structural Engineering. According to data from OpenAlex, Yutao Qi has authored 55 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 25 papers in Computational Theory and Mathematics and 13 papers in Civil and Structural Engineering. Recurrent topics in Yutao Qi's work include Advanced Multi-Objective Optimization Algorithms (25 papers), Metaheuristic Optimization Algorithms Research (23 papers) and Evolutionary Algorithms and Applications (11 papers). Yutao Qi is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (25 papers), Metaheuristic Optimization Algorithms Research (23 papers) and Evolutionary Algorithms and Applications (11 papers). Yutao Qi collaborates with scholars based in China, Australia and Singapore. Yutao Qi's co-authors include Xiaoliang Ma, Licheng Jiao, Fang Liu, Jianshe Wu, Jianyong Sun, Xiaodong Li, Maoguo Gong, Minglei Yin, Lingling Li and Qiguang Miao and has published in prestigious journals such as IEEE Access, Sensors and Pattern Recognition.

In The Last Decade

Yutao Qi

53 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

MOEA/D with Adaptive Weight Adjustment

2013 525 citations Yutao Qi, Xiaoliang Ma et al. profile →
A Multiobjective Evolutionary Algorithm Based on Decision Variable Analyses for Multiobjective Optimization Problems With Large-Scale Variables

2015 382 citations Xiaoliang Ma, Fang Liu et al. IEEE Transactions on Evolutionary Computation profile →

Peers

Countries citing papers authored by Yutao Qi

Since Specialization

Citations

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

Fields of papers citing papers by Yutao Qi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yutao Qi

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	A surrogate-assisted evolutionary algorithm with Gaussian process regression and diversity search for large-scale expensive optimization 2025 ·Applied Soft Computing ·Xiaoliang Ma, Ye Li, (unknown), (unknown), (unknown), Lei Wang, Yutao Qi, Jian Xiong	1
2	Enhanced Multifactorial Evolutionary Algorithm With Meme Helper-Tasks 2022 ·IEEE Transactions on Cybernetics ·Xiaoliang Ma, (unknown), Anmin Zhu, Xiaodong Li, Yanan Yu, Lei Wang, Yutao Qi, Zexuan Zhu	35
3	Merged Differential Grouping for Large-Scale Global Optimization 2022 ·IEEE Transactions on Evolutionary Computation ·Xiaoliang Ma, (unknown), Xiaodong Li, Lei Wang, Yutao Qi, Zexuan Zhu	33
4	A surrogate assisted evolutionary multitasking optimization algorithm 2022 ·Applied Soft Computing ·Shangqi Yang, Yutao Qi, Rui Yang, Xiaoliang Ma, Haibin Zhang	10
5	Enhancing evolutionary multitasking optimization by leveraging inter-task knowledge transfers and improved evolutionary operators 2022 ·Knowledge-Based Systems ·Xiaoliang Ma, (unknown), Yanan Yu, Hongjie Liu, Yan Wang, Lei Wang, Yutao Qi, Jian Xiong	11
6	Multiobjectivization of Single-Objective Optimization in Evolutionary Computation: A Survey 2021 ·IEEE Transactions on Cybernetics ·Xiaoliang Ma, (unknown), Xiaodong Li, Yutao Qi, Lei Wang, Zexuan Zhu	28
7	Improving Evolutionary Multitasking Optimization by Leveraging Inter-Task Gene Similarity and Mirror Transformation 2021 ·IEEE Computational Intelligence Magazine ·Xiaoliang Ma, (unknown), Zexuan Zhu, Xiaodong Li, Lei Wang, Yutao Qi, (unknown)	19
8	Self-Paced Dense Connectivity Learning for Visual Tracking 2019 ·IEEE Access ·(unknown), Jianfeng Song, Yutao Qi, (unknown), Qiguang Miao	3
9	Architectural Style Classification Based on Feature Extraction Module 2018 ·IEEE Access ·Peipei Zhao, Qiguang Miao, Jianfeng Song, Yutao Qi, Ruyi Liu, (unknown)	16
10	A Combinatorial Solution to Point Symbol Recognition 2018 ·Sensors ·Yining Quan, Yuanyuan Shi, Qiguang Miao, Yutao Qi	4
11	User-preference based decomposition in MOEA/D without using an ideal point 2018 ·Swarm and Evolutionary Computation ·Yutao Qi, Xiaodong Li, (unknown), Qiguang Miao	34
12	Enhancing robustness of the inverted PBI scalarizing method in MOEA/D 2017 ·Applied Soft Computing ·Yutao Qi, (unknown), Xiaodong Li, Yining Quan, Qiguang Miao	9
13	Maximizing Hydropower Generation in Flood Control Operation using Preference Based Multi-objective Evolutionary Algorithm 2017 ·IOP Conference Series Earth and Environmental Science ·Yutao Qi, (unknown), (unknown), Qiguang Miao	4
14	Approximating the irregularly shaped Pareto front of multi-objective reservoir flood control operation problem 2017 ·Applied Mathematical Modelling ·Jungang Luo, Xiaomei Sun, Yutao Qi, Jiancang Xie	11
15	Self-adaptive multi-objective evolutionary algorithm based on decomposition for large-scale problems: A case study on reservoir flood control operation 2016 ·Information Sciences ·Yutao Qi, Liang Bao, Xiaoliang Ma, Qiguang Miao, Xiaodong Li	41
16	A Multiobjective Evolutionary Algorithm Based on Decision Variable Analyses for Multiobjective Optimization Problems With Large-Scale Variables breakdown → 2015 ·IEEE Transactions on Evolutionary Computation ·Xiaoliang Ma, Fang Liu, Yutao Qi, Xiaodong Wang, Lingling Li, Licheng Jiao, Minglei Yin, Maoguo Gong	382
17	MOEA/D with opposition-based learning for multiobjective optimization problem 2014 ·Neurocomputing ·Xiaoliang Ma, Fang Liu, Yutao Qi, Maoguo Gong, Minglei Yin, Lingling Li, Licheng Jiao, Jianshe Wu	67
18	Hybrid Immune Algorithm with EDA for Multi-Objective Optimization 2014 ·Journal of Software ·Yutao Qi, (unknown), Jingle Liu, Yuan Ren, Licheng Jiao	1
19	Memory Based Lamarckian Evolutionary Algorithm for Job Shop Scheduling Problem 2011 ·Journal of Software ·(unknown), Fang Liu, Maoguo Gong, Yutao Qi	1
20	Discrete differential evolution algorithm for the job shop scheduling problem 2009 ·Fang Liu, Yutao Qi, (unknown), Hongxia Hao	8

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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