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Computer Science

D-Index
39
Citations
5195
World Ranking
9882
National Ranking
105

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
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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