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

D-Index & Metrics

Computer Science

D-Index
96
Citations
26529
World Ranking
449
National Ranking
59

Research.com Recognitions

  • 2026 - Research.com Computer Science in China Leader Award
  • 2025 - Research.com Computer Science in China Leader Award
  • 2022 - Research.com Computer Science in China Leader Award

Overview

Ling Wang is affiliated with Tsinghua University in China and has contributed extensively to research in engineering and computer science. Their work primarily intersects industrial and manufacturing engineering, artificial intelligence, computational theory and mathematics, electrical and electronic engineering, and aerospace engineering.

The scientist's research topics focus on scheduling and optimization algorithms, advanced manufacturing and logistics optimization, metaheuristic optimization algorithms, advanced multi-objective optimization, assembly line balancing optimization, vehicle routing optimization methods, and transportation and mobility innovations.

Ling Wang has published numerous papers in various reputable venues, including:

  • IEEE Transactions on Evolutionary Computation
  • IEEE Transactions on Systems Man and Cybernetics Systems
  • IEEE Transactions on Intelligent Transportation Systems
  • Swarm and Evolutionary Computation
  • IEEE Transactions on Emerging Topics in Computational Intelligence

Recent significant publications include:

  • "A Cooperative Memetic Algorithm With Learning-Based Agent for Energy-Aware Distributed Hybrid Flow-Shop Scheduling," 2021, IEEE Transactions on Evolutionary Computation
  • "Assessing the effects of China's Three-North Shelter Forest Program over 40 years," 2022, The Science of The Total Environment
  • "A Knowledge-Based Two-Population Optimization Algorithm for Distributed Energy-Efficient Parallel Machines Scheduling," 2020, IEEE Transactions on Cybernetics
  • "A Bi-Population Cooperative Memetic Algorithm for Distributed Hybrid Flow-Shop Scheduling," 2020, IEEE Transactions on Emerging Topics in Computational Intelligence
  • "A Generic Markov Decision Process Model and Reinforcement Learning Method for Scheduling Agile Earth Observation Satellites," 2020, IEEE Transactions on Systems Man and Cybernetics Systems

Frequent collaborators include Guohua Wu, Jingjing Wang, Jing-fang Chen, Rui Wang, and Zixiao Pan.

Best Publications

  • Improved particle swarm optimization combined with chaos

    Bo Liu;Ling Wang;Yi-Hui Jin;Fang Tang

  • An effective co-evolutionary particle swarm optimization for constrained engineering design problems

    Qie He;Ling Wang

  • An effective co-evolutionary differential evolution for constrained optimization

    Fu zhuo Huang;Ling Wang;Qie He

  • An Effective PSO-Based Memetic Algorithm for Flow Shop Scheduling

    Bo Liu;Ling Wang;Yi-Hui Jin

  • A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization

    Qie He;Ling Wang

  • An effective hybrid optimization strategy for job-shop scheduling problems

    Ling Wang;Da-Zhong Zheng

  • A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems

    Ling Wang;Quan-Ke Pan;P. N. Suganthan;Wen-Hong Wang

  • An effective hybrid PSO-based algorithm for flow shop scheduling with limited buffers

    Bo Liu;Ling Wang;Yi-Hui Jin

  • A Hybrid Quantum-Inspired Genetic Algorithm for Multiobjective Flow Shop Scheduling

    Bin-Bin Li;Ling Wang

  • Parameter extraction of photovoltaic models using an improved teaching-learning-based optimization

    Shuijia Li;Wenyin Gong;Xuesong Yan;Chengyu Hu

  • A Knowledge-Based Cooperative Algorithm for Energy-Efficient Scheduling of Distributed Flow-Shop

    Jing-Jing Wang;Ling Wang

  • An Effective Hybrid Heuristic for Flow Shop Scheduling

    D.-Z. Zheng;L. Wang

  • An effective artificial bee colony algorithm for the flexible job-shop scheduling problem

    Ling Wang;Gang Zhou;Ye Xu;Shengyao Wang

  • Effective heuristics and metaheuristics to minimize total flowtime for the distributed permutation flowshop problem

    Quan-Ke Pan;Quan-Ke Pan;Liang Gao;Ling Wang;Jing Liang

  • A novel binary fruit fly optimization algorithm for solving the multidimensional knapsack problem

    Ling Wang;Xiao-long Zheng;Sheng-yao Wang

  • An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem

    Sheng-yao Wang;Ling Wang;Min Liu;Ye Xu

  • A competitive memetic algorithm for multi-objective distributed permutation flow shop scheduling problem

    Jin Deng;Ling Wang

  • Parameter estimation for chaotic systems by particle swarm optimization

    Qie He;Ling Wang;Bo Liu

  • A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimisation

    Quan-Ke Pan;Quan-Ke Pan;Ling Wang;Jun-Qing Li;Jun-Qing Li;Jun-Hua Duan;Jun-Hua Duan

  • A review of energy-efficient scheduling in intelligent production systems

    Kaizhou Gao;Kaizhou Gao;Yun Huang;Ali Sadollah;Ling Wang

  • A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems

    Quan-Ke Pan;Ling Wang;Bin Qian

  • An Effective Artificial Bee Colony Algorithm for a Real-World Hybrid Flowshop Problem in Steelmaking Process

    Quan-Ke Pan;Ling Wang;Kun Mao;Jin-Hui Zhao

Frequent Co-Authors

Liang Gao
Liang Gao Huazhong University of Science and Technology
Wenyin Gong
Wenyin Gong China University of Geosciences
Junqing Li
Junqing Li Liaocheng University
Kaizhou Gao
Kaizhou Gao Macau University of Science and Technology
Xinyu Li
Xinyu Li Huazhong University of Science and Technology
Witold Pedrycz
Witold Pedrycz University of Alberta
Jing Liang
Jing Liang Zhengzhou University
Hisao Ishibuchi
Hisao Ishibuchi Southern University of Science and Technology
Yun Li
Yun Li University of Electronic Science and Technology of China

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