World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
5195
World Ranking
9881
National Ranking
105

S. G. Ponnambalam 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 S. G. Ponnambalam 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: 189 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

S. G. Ponnambalam 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 S. G. Ponnambalam 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

S. G. Ponnambalam is affiliated with Vellore Institute of Technology University in India. Their research spans several areas within engineering and business, management, and accounting, with a primary focus on industrial and manufacturing engineering. Their work addresses multiple subfields, including industrial and manufacturing engineering, strategy and management, management information systems, mechanical engineering, and computer networks and communications.

The scientist's research interests cover a range of topics involving sustainable and digital industrial processes. Key themes in their work include sustainable supply chain management, digital transformation in industry, assembly line balancing optimization, advanced manufacturing and logistics optimization, scheduling and optimization algorithms, recycling and waste management techniques, and quality and supply management.

Recent noteworthy publications by S. G. Ponnambalam include:

  • "Enhancing the adaptability: Lean and green strategy towards the Industry Revolution 4.0," 2020, Journal of Cleaner Production
  • "Cost-oriented robotic assembly line balancing problem with setup times: multi-objective algorithms," 2020, Journal of Intelligent Manufacturing
  • "Flowshop scheduling with sequence dependent setup times and batch delivery in supply chain," 2021, Computers & Industrial Engineering
  • "Analysing the Barriers Involved in Recycling the Textile Waste in India Using Fuzzy DEMATEL," 2023, Sustainability
  • "Energy aware semi-automatic assembly line balancing problem considering ergonomic risk and uncertain processing time," 2023, Expert Systems with Applications

The scientist has frequently published in venues such as Sustainability, Sadhana, International Journal of Robotics and Automation, Journal of Cleaner Production, and Journal of Intelligent Manufacturing.

Collaborations are a significant part of their research activity, with several frequent co-authors including Mukund Nilakantan Janardhanan, Bathrinath Sankaranarayanan, S. Saravanasankar, S. Bathrinath, and Hon Loong Lam.

S. G. Ponnambalam has also contributed to scholarly books, with one book titled "Innovation Analytics" published by WORLD SCIENTIFIC (EUROPE) eBooks in 2020.

Best Publications

  • A Multi-Objective Genetic Algorithm for Solving Assembly Line Balancing Problem

    S. G. Ponnambalam;P. Aravindan;G. Mogileeswar Naidu

  • A hybrid cuckoo search and genetic algorithm for reliability-redundancy allocation problems

    G. Kanagaraj;S. G. Ponnambalam;N. Jawahar

  • An extensive review of research in swarm robotics

    Yogeswaran Mohan;S. G. Ponnambalam

  • Review on life cycle inventory: methods, examples and applications

    Samantha Islam;S.G. Ponnambalam;Hon Loong Lam

  • An investigation on minimizing cycle time and total energy consumption in robotic assembly line systems

    J. Mukund Nilakantan;George Q. Huang;S.G. Ponnambalam

  • A comparative evaluation of assembly line balancing Heuristics

    S. G Ponnambalam;P. Aravindan;G. Mogileeswar Naidu

  • A multiobjective genetic algorithm for job shop scheduling

    S.G. Ponnambalam;V. Ramkumar;N. Jawahar

  • A Tabu Search Algorithm for Job Shop Scheduling

    S. G. Ponnambalam;P. Aravindan;S. V. Rajesh

  • Evolutionary algorithms for scheduling m-machine flow shop with lot streaming

    S. Marimuthu;S. G. Ponnambalam;N. Jawahar

  • A TSP-GA multi-objective algorithm for flow-shop scheduling

    S. G. Ponnambalam;H. Jagannathan;M. Kataria;A. Gadicherla

  • Genetic algorithms for sequencing problems in mixed model assembly lines

    S. G. Ponnambalam;P. Aravindan;M. Subba Rao

  • Threshold accepting and Ant-colony optimization algorithms for scheduling m-machine flow shops with lot streaming

    S. Marimuthu;S.G. Ponnambalam;N. Jawahar

  • Robotic U-shaped assembly line balancing using particle swarm optimization

    J. Mukund Nilakantan;S.G. Ponnambalam

  • Enhancing the adaptability: Lean and green strategy towards the Industry Revolution 4.0

    Wei Dong Leong;Sin Yong Teng;Bing Shen How;Sue Lin Ngan

  • A simulated annealing algorithm for job shop scheduling

    S. G. Ponnambalam;N. Jawahar;P. Aravindan

  • Multi-objective genetic algorithm as channel selection method for P300 and motor imagery data set

    Chea-Yau Kee;S.G. Ponnambalam;Chu-Kiong Loo

  • Comparative evaluation of genetic algorithms for job-shop scheduling

    S. G. Ponnambalam;P. Aravindan;P. Sreenivasa Rao

  • Obstacle avoidance control of redundant robots using variants of particle swarm optimization

    Goh Shyh Chyan;S. G. Ponnambalam

  • A genetic algorithm for scheduling flexible manufacturing systems

    N. Jawahar;P. Aravindan;S. G. Ponnambalam

  • Mobile robot path planning using ant colony optimization

    Yee Zi Cong;S. G. Ponnambalam

  • Constructive and improvement flow shop scheduling heuristics: An extensive evaluation

    S. G. Ponnambalam;P. Aravindan;S. Chandrasekaran

Frequent Co-Authors

Hon Loong Lam
Hon Loong Lam University of Nottingham Malaysia Campus
Nachiappan Subramanian
Nachiappan Subramanian University of Sussex
Peter V. Nielsen
Peter V. Nielsen Aalborg University
Manoj Kumar Tiwari
Manoj Kumar Tiwari Indian Institute of Technology Kharagpur
George Q. Huang
George Q. Huang Hong Kong Polytechnic University
Siba Sankar Mahapatra
Siba Sankar Mahapatra National Institute of Technology Rourkela
Kazuhiro Izui
Kazuhiro Izui Kyoto University
Angappa Gunasekaran
Angappa Gunasekaran Penn State Harrisburg
Amir H. Gandomi
Amir H. Gandomi University of Technology Sydney

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