World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
8921
World Ranking
4911
National Ranking
660

Kaizhou Gao publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Kaizhou Gao sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 235 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Kaizhou Gao D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Kaizhou Gao sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Kaizhou Gao is affiliated with Macau University of Science and Technology in China. Their research work is primarily situated within the field of Engineering, with a strong emphasis on Industrial and Manufacturing Engineering as well as Control and Systems Engineering.

The scientist's contributions extend notably into the domain of Artificial Intelligence and Computer Networks and Communications, reflecting a multidisciplinary approach to complex engineering problems.

Kaizhou Gao's research topics cover a variety of subjects, including:

  • Scheduling and Optimization Algorithms
  • Advanced Manufacturing and Logistics Optimization
  • Assembly Line Balancing Optimization
  • Vehicle Routing Optimization Methods
  • Manufacturing Process and Optimization
  • Transportation Planning and Optimization
  • Optimization and Search Problems

Frequent collaborative partnerships have been established with researchers such as Yaping Fu, Yuyan Han, Junqing Li, Ponnuthurai Nagaratnam Suganthan, and Yuting Wang.

The scientist has published extensively in several scholarly venues, with a notable concentration of works appearing in:

  • Swarm and Evolutionary Computation
  • Expert Systems with Applications
  • Applied Soft Computing
  • IEEE Transactions on Intelligent Transportation Systems
  • IEEE Transactions on Systems Man and Cybernetics Systems

Key recent papers authored or co-authored by Kaizhou Gao include:

  • "Distributed scheduling problems in intelligent manufacturing systems," 2021, Tsinghua Science & Technology
  • "A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem," 2020, IEEE Transactions on Intelligent Transportation Systems
  • "An Improved Artificial Bee Colony Algorithm With Q-Learning for Solving Permutation Flow-Shop Scheduling Problems," 2022, IEEE Transactions on Systems Man and Cybernetics Systems
  • "A Hybrid Iterated Greedy Algorithm for a Crane Transportation Flexible Job Shop Problem," 2021, IEEE Transactions on Automation Science and Engineering
  • "A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances," 2022, IEEE Transactions on Intelligent Transportation Systems

Best Publications

  • A review on swarm intelligence and evolutionary algorithms for solving flexible job shop scheduling problems

    Kaizhou Gao;Zhiguang Cao;Le Zhang;Zhenghua Chen

  • Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems

    Jun-Qing Li;Quan-Ke Pan;Quan-Ke Pan;Kai-Zhou Gao

  • Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions

    Jun-qing Li;Jun-qing Li;Jun-qing Li;Hong-yan Sang;Yu-yan Han;Cun-gang Wang

  • Flexible Job-Shop Rescheduling for New Job Insertion by Using Discrete Jaya Algorithm

    Kaizhou Gao;Fajun Yang;MengChu Zhou;Quanke Pan

  • A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion

    Kai Zhou Gao;Ponnuthurai Nagaratnam Suganthan;Tay Jin Chua;Chin Soon Chong

  • A review of energy-efficient scheduling in intelligent production systems

    Kaizhou Gao;Kaizhou Gao;Yun Huang;Ali Sadollah;Ling Wang

  • Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling

    Kai-Zhou Gao;Kai-Zhou Gao;Ponnuthurai N. Suganthan;Quan-Ke Pan;Tay Jin Chua

  • Discrete harmony search algorithm for flexible job shop scheduling problem with multiple objectives

    K. Z. Gao;P. N. Suganthan;Q. K. Pan;T. J. Chua

  • Distributed Scheduling Problems in Intelligent Manufacturing Systems

    Yaping Fu;Yushuang Hou;Zifan Wang;Xinwei Wu

  • An improved artificial bee colony algorithm for flexible job-shop scheduling problem with fuzzy processing time

    Kai Zhou Gao;Ponnuthurai Nagaratnam Suganthan;Quan Ke Pan;Tay Jin Chua

  • Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times

    Unknown

  • An Improved Artificial Bee Colony Algorithm With Q-Learning for Solving Permutation Flow-Shop Scheduling Problems

    Unknown

  • Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion

    Kai Zhou Gao;Kai Zhou Gao;Ponnuthurai Nagaratnam Suganthan;Quan Ke Pan;Mehmet Fatih Tasgetiren

  • A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem

    Palwasha W. Shaikh;Mohammed El-Abd;Mounib Khanafer;Kaizhou Gao

  • A Hybrid Iterated Greedy Algorithm for a Crane Transportation Flexible Job Shop Problem

    Jun-Qing Li;Yu Du;Kai-Zhou Gao;Pei-Yong Duan

  • Effective invasive weed optimization algorithms for distributed assembly permutation flowshop problem with total flowtime criterion

    Hong-Yan Sang;Quan-Ke Pan;Jun-Qing Li;Ping Wang

  • A genetic programming hyper-heuristic approach for the multi-skill resource constrained project scheduling problem

    Jian Lin;Lei Zhu;Kaizhou Gao;Kaizhou Gao

  • A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances

    Unknown

  • Effective metaheuristics for scheduling a hybrid flowshop with sequence-dependent setup times

    Quan-Ke Pan;Liang Gao;Xin-Yu Li;Kai-Zhou Gao

  • A survey on meta-heuristics for solving disassembly line balancing, planning and scheduling problems in remanufacturing

    Kai-Zhou Gao;Kai-Zhou Gao;Z. M. He;Y. Huang;Pei-Yong Duan

  • Discrete harmony search algorithm for the no-wait flow shop scheduling problem with total flow time criterion

    Kai-zhou Gao;Quan-ke Pan;Jun-qing Li

  • Discrete evolutionary multi-objective optimization for energy-efficient blocking flow shop scheduling with setup time

    Yuyan Han;Junqing Li;Junqing Li;Hongyan Sang;Yiping Liu

  • An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time

    Kai Zhou Gao;Ponnuthurai Nagaratnam Suganthan;Quan Ke Pan;Mehmet Fatih Tasgetiren

Frequent Co-Authors

Junqing Li
Junqing Li Liaocheng University
Quan-Ke Pan
Quan-Ke Pan Shanghai University
Rong Su
Rong Su Nanyang Technological University
Yi Zhang
Yi Zhang Nanyang Technological University
NaiQi Wu
NaiQi Wu Macau University of Science and Technology
Jing Liang
Jing Liang Zhengzhou University
Ling Wang
Ling Wang Tsinghua University
Le Zhang
Le Zhang University of Electronic Science and Technology of China
MengChu Zhou
MengChu Zhou New Jersey Institute of Technology

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