World's Best Scientists 2026 revealed!
Liang-Yuh Ouyang

Liang-Yuh Ouyang

D-Index & Metrics

Engineering and Technology

D-Index
55
Citations
8877
World Ranking
3084
National Ranking
19

Liang-Yuh Ouyang publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Liang-Yuh Ouyang sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 142 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Liang-Yuh Ouyang D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Liang-Yuh Ouyang sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 55 D-Index — 70th percentile

70% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Liang-Yuh Ouyang is affiliated with Tamkang University in Taiwan. Their research broadly falls within the field of Business, Management and Accounting, with a particular emphasis on Management Information Systems, Strategy and Management, Industrial and Manufacturing Engineering, Environmental Engineering, and Computer Vision and Pattern Recognition.

The scientist's recent publications focus mainly on supply chain and inventory management, sustainable supply chain management, and related optimization techniques. Topics explored include quality and supply management, advanced queuing theory analysis, scheduling and optimization algorithms, remote sensing and LiDAR applications, as well as image processing and 3D reconstruction.

Ouyang's recent papers include the following:

  • Integrated inventory model involving quality improvement investment and advance-cash-credit payments (2021, RAIRO - Operations Research)
  • Deteriorating inventory model with advance-cash-credit payment schemes and partial backlogging (2025, Soft Computing)
  • Estimating Forest Carbon Stock Using Enhanced ResNet and Sentinel-2 Imagery (2025, Forests)
  • Assessment of commanders' situation awareness: a study based on SEEV, QN-ACTR, and cognitive load (2025, Displays)

The frequent co-authors collaborating with Ouyang include:

  • Chih-Te Yang
  • Chien-Hsiu Huang
  • Chun-Tao Chang
  • Mei-Chuan Cheng
  • Jintong Ren

Ouyang has published work in several academic venues such as:

  • RAIRO - Operations Research
  • Soft Computing
  • Forests
  • Displays

The scientist's research contributions involve diverse applications that intersect supply chain optimization and environmental considerations. This includes integrating quality improvement investments into inventory models alongside payment schemes. Their work extends into environmental engineering through remote sensing and image analysis for forest carbon stock estimation.

Best Publications

  • An optimal replenishment policy for non-instantaneous deteriorating items with stock-dependent demand and partial backlogging

    Kun-Shan Wu;Liang-Yuh Ouyang;Chih-Te Yang

  • Mixture Inventory Model with Backorders and Lost Sales for Variable Lead Time

    Liang-Yuh Ouyang;Neng-Che Yeh;Kun-Shan Wu

  • AN EOQ MODEL FOR DETERIORATING ITEMS UNDER SUPPLIER CREDITS LINKED TO ORDERING QUANTITY

    Chun-Tao Chang;Liang-Yuh Ouyang;Jinn-Tsair Teng

  • A study on an inventory model for non-instantaneous deteriorating items with permissible delay in payments

    Liang-Yuh Ouyang;Kun-Shan Wu;Chih-Te Yang

  • Integrated vendor–buyer cooperative models with stochastic demand in controllable lead time

    Liang-Yuh Ouyang;Kun-Shan Wu;Chia-Huei Ho

  • Optimal credit period and lot size for deteriorating items with expiration dates under two-level trade credit financing

    Jiang Wu;Liang-Yuh Ouyang;Leopoldo Eduardo Cárdenas-Barrón;Suresh Kumar Goyal

  • An EOQ model for perishable items under stock-dependent selling rate and time-dependent partial backlogging

    Chung-Yuan Dye;Liang-Yuh Ouyang

  • INTEGRATED VENDOR-BUYER COOPERATIVE INVENTORY MODELS WITH CONTROLLABLE LEAD TIME AND ORDERING COST REDUCTION

    Hung-Chi Chang;Liang-Yuh Ouyang;Kun-Shan Wu;Chia-Huei Ho

  • An economic order quantity model for deteriorating items with partially permissible delay in payments linked to order quantity

    Liang-Yuh Ouyang;Jinn-Tsair Teng;Suresh Kumar Goyal;Chih-Te Yang

  • Mixture inventory model involving variable lead time with a service level constraint

    Liang-Yuh Ouyang;Kun-Shan Wu

  • An integrated vendor–buyer inventory model with quality improvement and lead time reduction

    Liang-Yuh Ouyang;Kun-Shan Wu;Chia-Huei Ho

  • Deterministic inventory model for deteriorating items with capacity constraint and time-proportional backlogging rate

    Chung-Yuan Dye;Liang-Yuh Ouyang;Tsu-Pang Hsieh

  • Quality improvement, setup cost and lead-time reductions in lot size reorder point models with an imperfect production process

    Liang-Yuh Ouyang;Cheng-Kang Chen;Hung-Chi Chang

  • Determining optimal selling price and lot size with a varying rate of deterioration and exponential partial backlogging

    Chung-Yuan Dye;Tsu-Pang Hsieh;Liang-Yuh Ouyang

  • Determining optimal lot size for a two-warehouse system with deterioration and shortages using net present value

    Tsu-Pang Hsieh;Chung-Yuan Dye;Liang-Yuh Ouyang

  • Fuzzy mixture inventory model involving fuzzy random variable lead time demand and fuzzy total demand

    Hung-Chi Chang;Jing-Shing Yao;Liang-Yuh Ouyang

  • Retailer’s optimal pricing and lot-sizing policies for deteriorating items with partial backlogging

    Horng-Jinh Chang;Jinn-Tsair Teng;Liang-Yuh Ouyang;Chung-Yuan Dye

  • Lead time and ordering cost reductions in continuous review inventory systems with partial backorders

    Liang-Yuh Ouyang;Cheng-Kang Chen;Hung-Chi Chang

  • Optimal production lot with imperfect production process under permissible delay in payments and complete backlogging

    Liang-Yuh Ouyang;Chun-Tao Chang

  • An inventory model for deteriorating items with exponential declining demand and partial backlogging

    Liang-Yuh Ouyang;Kun-Shan Wu;Mei-Chuan Cheng

  • An EOQ model for deteriorating items under trade credits

    Liang-Yuh Ouyang;C.-T. Chang;J.-T. Teng

  • On an EOQ model for deteriorating items with time-varying demand and partial backlogging

    J.-T. Teng;H.-L. Yang;Liang-Yuh Ouyang

Frequent Co-Authors

Jinn-Tsair Teng
Jinn-Tsair Teng William Paterson University
Kun-Shan Wu
Kun-Shan Wu Tamkang University
Chung-Yuan Dye
Chung-Yuan Dye National Taiwan Ocean University
Kuen-Suan Chen
Kuen-Suan Chen National Chin-Yi University of Technology
Leopoldo Eduardo Cárdenas-Barrón
Leopoldo Eduardo Cárdenas-Barrón Monterrey Institute of Technology and Higher Education
Suresh Kumar Goyal
Suresh Kumar Goyal Concordia University

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