Jun Liu

Orcid: 0000-0002-7409-8675

Affiliations:
  • Huazhong University of Science and Technology, School of Naval Architecture and Ocean Engineering, Wuhan, China


According to our database1, Jun Liu authored at least 12 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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2020
2021
2022
2023
2024
2025
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Links

Online presence:

On csauthors.net:

Bibliography

2025
A Surrogate-Assisted Constrained Optimization Evolutionary Algorithm by Searching Multiple Kinds of Global and Local Regions.
IEEE Trans. Evol. Comput., February, 2025

2024
Bi-Population-Enhanced Cooperative Differential Evolution for Constrained Large-Scale Optimization Problems.
IEEE Trans. Evol. Comput., December, 2024

2023
A coevolutionary algorithm assisted by two archives for constrained multi-objective optimization problems.
Swarm Evol. Comput., October, 2023

2022
A novel fidelity selection strategy-guided multifidelity kriging algorithm for structural reliability analysis.
Reliab. Eng. Syst. Saf., 2022

Cooperative Bayesian optimization with hybrid grouping strategy and sample transfer for expensive large-scale black-box problems.
Knowl. Based Syst., 2022

An efficient global optimization algorithm for expensive constrained black-box problems by reducing candidate infilling region.
Inf. Sci., 2022

A sequential multi-fidelity surrogate model-assisted contour prediction method for engineering problems with expensive simulations.
Eng. Comput., 2022

2021
An efficient constrained global optimization algorithm with a clustering-assisted multiobjective infill criterion using Gaussian process regression for expensive problems.
Inf. Sci., 2021

2020
A sequential constraints updating approach for Kriging surrogate model-assisted engineering optimization design problem.
Eng. Comput., 2020

An adaptive constraint-handling approach for optimization problems with expensive objective and constraints.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019
A Three-Stage Surrogate Model Assisted Multi-Objective Genetic Algorithm for Computationally Expensive Problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2019

2017
Expected Improvement Matrix-Based Infill Criteria for Expensive Multiobjective Optimization.
IEEE Trans. Evol. Comput., 2017


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