Jing-Yu
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Jing-Yu JI, Jeff

Jeff Ji serves as a Research Assistant Professor in the Department of Computing & Decision Sciences at Lingnan University, Hong Kong. He primarily focuses on areas like multimodal optimization, constrained optimization, and expensive optimization. Presently, his research endeavors delve into the utilization of deep learning regression models and the application of parallel computing to address optimization problems that are resource-intensive and time-consuming.

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Research

I'm interested in developing efficient evolutionary models and algorithms for constrained optimization, multimodal optimization, and expensive optimization, etc.

Journal Papers:

  1. Region division and merging-based multiobjective optimization for multimodal optimization problems
    Jing-Yu Ji, Sanyou Zeng, and Man-Leung Wong
    Applied Soft Computing, 2024
  2. An ε-constrained multiobjective differential evolution with adaptive gradient-based repair method for real-world constrained optimization problems
    Jing-Yu Ji, Zusheng Tan, Sanyou Zeng, and Man-Leung Wong
    Applied Soft Computing, 2024
  3. A Surrogate-Assisted Evolutionary Algorithm for Seeking Multiple Solutions of Expensive Multimodal Optimization Problems
    Jing-Yu Ji, Zusheng Tan, Sanyou Zeng, Eric W.K.See-To, and Man-Leung Wong
    IEEE TETCI, 2023 | paper | code
  4. Decomposition-based multiobjective optimization for nonlinear equation systems with many and infinitely many roots
    Jing-Yu Ji and Man-Leung Wong
    Information Sciences, 2022
  5. ε-Constrained multiobjective differential evolution using linear population size expansion
    Jing-Yu Ji, Sanyou Zeng, and Man-Leung Wong
    Information Sciences, 2022
  6. An improved dynamic multi-objective optimization approach for nonlinear equation systems
    Jing-Yu Ji and Man-Leung Wong
    Information Sciences, 2021
  7. Density-Enhanced Multiobjective Evolutionary Approach for Power Economic Dispatch Problems
    Jing-Yu Ji, Wei-Jie Yu, Jinghui Zhong, Jun Zhang
    IEEE TSMC: Systems, 2021 | paper
  8. Multiobjective optimization with ϵ-constrained method for solving real-parameter constrained optimization problems
    Jing-Yu Ji, Wei-Jie Yu, Yue-Jiao Gong, and Jun Zhang
    Information Sciences, 2018
  9. A tri-objective differential evolution approach for multimodal optimization
    Wei-Jie Yu, Jing-Yu Ji, Wei-Jie Yu, Yue-Jiao Gong, Qiang Yang, and Jun Zhang
    Information Sciences, 2018

Conference Papers:

  1. Surrogate-assisted Parameter Re-initialization for Differential Evolution
    Jing-Yu Ji and Man-Leung Wong
    IEEE Symposium Series on Computational Intelligence, 2022
  2. Solving Nonlinear Equation Systems Using Multiobjective Differential Evolution
    Jing-Yu Ji, Wei-Jie Yu, and Jun Zhang
    International Conference on Evolutionary Multi-Criterion Optimization, 2019
  3. A two-stage coevolution approach for constrained optimization
    Jing-Yu Ji, Wei-Jie Yu, and Jun Zhang
    Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2017
  4. Solving multimodal optimization problems through a multiobjective optimization approach
    Jing-Yu Ji, Wei-Jie Yu, Wei-Neng Chen, Zhi-Hui Zhan, and Jun Zhang
    Seventh International Conference on Information Science and Technology, 2017

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