Sheng-Hao Wu

Orcid: 0000-0002-4312-2521

According to our database1, Sheng-Hao Wu authored at least 14 papers between 2021 and 2025.

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

Timeline

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Links

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Bibliography

2025
Learning to Transfer for Evolutionary Multitasking.
IEEE Trans. Cybern., July, 2025

Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap.
IEEE Trans. Evol. Comput., April, 2025

Traffic Flow Dataset for "Traffic Signal Timing Optimization: From Evolution to Adaptation".
Dataset, January, 2025

2024
Advancing Automated Knowledge Transfer in Evolutionary Multitasking via Large Language Models.
CoRR, 2024

Towards Next Era of Multi-objective Optimization: Large Language Models as Architects of Evolutionary Operators.
CoRR, 2024

Unlock the Power of Algorithm Features: A Generalization Analysis for Algorithm Selection.
CoRR, 2024

2023
Transferable Adaptive Differential Evolution for Many-Task Optimization.
IEEE Trans. Cybern., November, 2023

Orthogonal Transfer for Multitask Optimization.
IEEE Trans. Evol. Comput., February, 2023

Diversity-driven Multi-population Particle Swarm Optimization for Dynamic Optimization Problem.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Multi-View Transfer with Marginal and Conditional Alignment for Many-Task Optimization.
Proceedings of the IEEE Congress on Evolutionary Computation, 2023

2022
An Adaptive Ant Colony System Based on Variable Range Receding Horizon Control for Berth Allocation Problem.
IEEE Trans. Intell. Transp. Syst., 2022

2021
SAFE: Scale-Adaptive Fitness Evaluation Method for Expensive Optimization Problems.
IEEE Trans. Evol. Comput., 2021

A New Evolutionary Computation Framework for Privacy-Preserving Optimization.
Proceedings of the 13th International Conference on Advanced Computational Intelligence, 2021

Historical Information-based Differential Evolution for Dynamic Optimization Problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021


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