World's Best Scientists 2026 revealed!
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Computer Science
Japan
2026

D-Index & Metrics

Computer Science

D-Index
77
Citations
41983
World Ranking
1233
National Ranking
6

Mitsuo Gen 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 Mitsuo Gen 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: 549 publications — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Mitsuo Gen 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 Mitsuo Gen 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: 77 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Computer Science in Japan Leader Award
  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2023 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award
  • 2016 - IEEE Transactions on Semiconductor Manufacturing Best Paper Award

Overview

Mitsuo Gen is affiliated with the Tokyo University of Science in Japan. Their research work primarily spans the fields of Engineering, Computer Science, and Business, Management and Accounting. The main subfields of study include Industrial and Manufacturing Engineering, Artificial Intelligence, Strategy and Management, Computational Theory and Mathematics, and Management Information Systems.

The scientist's research focuses on topics such as Scheduling and Optimization Algorithms, Advanced Manufacturing and Logistics Optimization, Metaheuristic Optimization Algorithms Research, Advanced Multi-Objective Optimization Algorithms, Assembly Line Balancing Optimization, Sustainable Supply Chain Management, and Supply Chain and Inventory Management.

Frequent co-authors collaborating with Mitsuo Gen include Wenqiang Zhang, Guohui Zhang, Jianquan Guo, YoungSu Yun, and Weidong Yang.

Common publication venues where Mitsuo Gen's work appears are:

  • Computers & Industrial Engineering
  • International Journal of Management Science and Engineering Management
  • Mathematical Biosciences & Engineering
  • International Journal of Internet Manufacturing and Services
  • Frontiers in Industrial Engineering

Notable recent papers published by Mitsuo Gen include:

  • Research on green closed-loop supply chain with the consideration of double subsidy in e-commerce environment, 2020, Computers & Industrial Engineering
  • A multiobjective memetic algorithm with particle swarm optimization and Q-learning-based local search for energy-efficient distributed heterogeneous hybrid flow-shop scheduling problem, 2023, Expert Systems with Applications
  • Multi-objective multi-mode resource-constrained project scheduling with fuzzy activity durations in prefabricated building construction, 2021, Computers & Industrial Engineering
  • Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach, 2020, Mathematics
  • Multidirection Update-Based Multiobjective Particle Swarm Optimization for Mixed No-Idle Flow-Shop Scheduling Problem, 2021, Complex System Modeling and Simulation

Best Publications

  • Genetic algorithms and engineering optimization

    Mitsuo Gen;Runwei Cheng

  • Genetic Algorithms

    Mitsuo Gen;Runwei Cheng

  • Genetic algorithms and engineering design

    Unknown

  • A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation

    Runwei Cheng;Mitsuo Gen;Yasuhiro Tsujimura

  • A genetic algorithm approach for multi-objective optimization of supply chain networks

    Fulya Altiparmak;Mitsuo Gen;Lin Lin;Turan Paksoy

  • Network Models and Optimization: Multiobjective Genetic Algorithm Approach

    Mitsuo Gen;Runwei Cheng;Lin Lin

  • A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems

    Jie Gao;Linyan Sun;Mitsuo Gen

  • A tutorial survey of job-shop scheduling problems using genetic algorithms, part II: hybrid genetic search strategies

    Runwei Cheng;Mitsuo Gen;Yasuhiro Tsujimura

  • Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach

    Admi Syarif;YoungSu Yun;Mitsuo Gen

  • A genetic algorithm for two-stage transportation problem using priority-based encoding

    Mitsuo Gen;Fulya Altiparmak;Lin Lin

  • Intelligent Engineering Systems Through Artificial Neural Networks

    Cihan H. Dagli;K. Mark Bryden;Steven M. Corns;Mitsuo Gen

  • A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries

    A. Serdar Tasan;Mitsuo Gen

  • A steady-state genetic algorithm for multi-product supply chain network design

    Fulya Altiparmak;Mitsuo Gen;Lin Lin;Ismail Karaoglan

  • A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems

    Jie Gao;Mitsuo Gen;Linyan Sun;Xiaohui Zhao

  • Genetic algorithm approach on multi-criteria minimum spanning tree problem

    Gengui Zhou;Mitsuo Gen

  • Genetic algorithm for non-linear mixed integer programming problems and its applications

    Takao Yokota;Mitsuo Gen;Yin-Xiu Li

  • Network model and optimization of reverse logistics by hybrid genetic algorithm

    Jeong-Eun Lee;Mitsuo Gen;Kyong-Gu Rhee

  • Hybrid genetic algorithm for multi-time period production/distribution planning

    Mitsuo Gen;Admi Syarif

  • The balanced allocation of customers to multiple distribution centers in the supply chain network: a genetic algorithm approach

    Gengui Zhou;Hokey Min;Mitsuo Gen

  • Soft computing approach for reliability optimization: State-of-the-art survey

    Mitsuo Gen;YoungSu Yun

  • Genetic algorithms for solving shortest path problems

    M. Gen;Runwei Cheng;Dingwei Wang

  • Foundations of Genetic Algorithms

    Mitsuo Gen;Mitsuo Gen;Runwei Cheng

Frequent Co-Authors

Chen-Fu Chien
Chen-Fu Chien National Tsing Hua University
Hisao Ishibuchi
Hisao Ishibuchi Southern University of Science and Technology
Hark Hwang
Hark Hwang Korea Advanced Institute of Science and Technology
Hokey Min
Hokey Min Bowling Green State University
Baoding Liu
Baoding Liu Tsinghua University
Kap Hwan Kim
Kap Hwan Kim Pusan National University
Reza Tavakkoli-Moghaddam
Reza Tavakkoli-Moghaddam University of Tehran
Sang M. Lee
Sang M. Lee University of Nebraska–Lincoln
Gwo-Hshiung Tzeng
Gwo-Hshiung Tzeng National Taipei University
Jiuping Xu
Jiuping Xu Sichuan University

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