World's Best Scientists 2026 revealed!
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Mathematics
Taiwan
2026
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Engineering and Technology
Taiwan
2022

D-Index & Metrics

Mathematics

D-Index
53
Citations
7400
World Ranking
923
National Ranking
5

Engineering and Technology

D-Index
53
Citations
7443
World Ranking
3514
National Ranking
25

Chin-Chia Wu publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Chin-Chia Wu sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 187 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Chin-Chia Wu D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Chin-Chia Wu sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 53 D-Index — 76th percentile

76% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Mathematics in Taiwan Leader Award
  • 2025 - Research.com Mathematics in Taiwan Leader Award
  • 2022 - Research.com Engineering and Technology in Taiwan Leader Award

Overview

Chin-Chia Wu is affiliated with Feng Chia University in Taiwan and conducts research primarily in the field of engineering. Their work focuses extensively on industrial and manufacturing engineering, with additional contributions in computer networks and communications, oncology, molecular biology, and artificial intelligence.

The main topics of their research include:

  • Scheduling and Optimization Algorithms
  • Advanced Manufacturing and Logistics Optimization
  • Assembly Line Balancing Optimization
  • Optimization and Search Problems
  • Optimization and Packing Problems
  • Metaheuristic Optimization Algorithms Research
  • Gut microbiota and health

The researcher has published in a number of journals, with frequent contributions to the following venues:

  • Mathematics
  • Swarm and Evolutionary Computation
  • International Journal of Production Research
  • Computers & Industrial Engineering
  • Engineering Optimization

Notable recent papers authored or coauthored by Chin-Chia Wu include:

  • Several variants of simulated annealing hyper-heuristic for a single-machine scheduling with two-scenario-based dependent processing times (2020, Swarm and Evolutionary Computation)
  • Robust scheduling for a two-stage assembly shop with scenario-dependent processing times (2020, International Journal of Production Research)
  • A robust customer order scheduling problem along with scenario-dependent component processing times and due dates (2020, Journal of Manufacturing Systems)

Frequent collaborators include:

  • Win-Chin Lin
  • Danyu Bai
  • Xingong Zhang
  • Shuenn-Ren Cheng
  • Jianyou Xu

The body of work contributed by Chin-Chia Wu addresses various aspects of optimization, particularly in scheduling and logistics contexts within manufacturing systems. Their research approach often involves metaheuristic and advanced algorithmic strategies to solve complex real-world production and assembly problems.

Best Publications

  • Some scheduling problems with sum-of-processing-times-based and job-position-based learning effects

    T.C. Edwin Cheng;Chin-Chia Wu;Wen-Chiung Lee

  • Some scheduling problems with deteriorating jobs and learning effects

    T. C. E. Cheng;Chin-Chia Wu;Wen-Chiung Lee

  • Minimizing total completion time in a two-machine flowshop with a learning effect

    W Lee

  • A bi-criterion single-machine scheduling problem with learning considerations

    Wen-Chiung Lee;Chin-Chia Wu;Hua-Jung Sung

  • A two-agent single-machine scheduling problem with truncated sum-of-processing-times-based learning considerations

    T. C. E. Cheng;Shuenn-Ren Cheng;Wen-Hung Wu;Peng-Hsiang Hsu

  • Scheduling problems with deteriorating jobs and learning effects including proportional setup times

    T. C. E. Cheng;Wen-Chiung Lee;Chin-Chia Wu

  • Single-machine scheduling problems with a learning effect

    Chin-Chia Wu;Wen-Chiung Lee

  • Single-machine scheduling with sum-of-logarithm-processing-times-based learning considerations

    T.C.E. Cheng;Peng-Jen Lai;Chin-Chia Wu;Wen-Chiung Lee

  • Single-machine and flowshop scheduling with a general learning effect model

    Chin-Chia Wu;Wen-Chiung Lee

  • A single-machine learning effect scheduling problem with release times

    Wen-Chiung Lee;Chin-Chia Wu;Peng-Hsiang Hsu

  • Scheduling linear deteriorating jobs to minimize makespan with an availability constraint on a single machine

    Chin-Chia Wu;Wen-Chiung Lee

  • Single-machine group-scheduling problems with deteriorating setup times and job-processing times

    Chin-Chia Wu;Wen-Chiung Lee

  • Some single-machine and m-machine flowshop scheduling problems with learning considerations

    Wen-Chiung Lee;Chin-Chia Wu

  • Scheduling with Time-Dependent Processing Times 2015

    Yunqiang Yin;T. C. E. Cheng;Chin-Chia Wu

  • A note on single-machine group scheduling problems with position-based learning effect

    Wen-Chiung Lee;Chin-Chia Wu

  • Single-machine batch delivery scheduling with an assignable common due window

    Yunqiang Yin;T.C.E. Cheng;Chou-Jung Hsu;Chin-Chia Wu

  • Scheduling problems with two agents and a linear non-increasing deterioration to minimize earliness penalties

    Yunqiang Yin;Shuenn-Ren Cheng;Chin-Chia Wu

  • Two-agent single-machine scheduling to minimize the batch delivery cost

    Yunqiang Yin;Yan Wang;T.C.E. Cheng;Du-Juan Wang

  • A simulated annealing approach to makespan minimization on identical parallel machines

    Wen-Chiung Lee;Chin-Chia Wu;Peter Chen

  • Single-machine group scheduling problems with deterioration consideration

    Chin-Chia Wu;Yau-Ren Shiau;Wen-Chiung Lee

  • Two-machine flowshop scheduling with a truncated learning function to minimize the makespan

    T.C.E. Cheng;Chin-Chia Wu;Juei-Chao Chen;Wen-Hsiang Wu

Frequent Co-Authors

Wen-Chiung Lee
Wen-Chiung Lee Feng Chia University
T.C.E. Cheng
T.C.E. Cheng Hong Kong Polytechnic University
Jatinder N. D. Gupta
Jatinder N. D. Gupta University of Alabama in Huntsville
Ling Wang
Ling Wang Tsinghua University
Xuerong Mao
Xuerong Mao University of Strathclyde

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