A Two-Phase Kriging-Assisted Evolutionary Algorithm for Expensive Constrained Multiobjective Optimization Problems-Reference-Cited by-同舟云学术

A Two-Phase Kriging-Assisted Evolutionary Algorithm for Expensive Constrained Multiobjective Optimization Problems

Published:2024-08 Issue:8 Volume:54 Page:4579-4591
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Zhang Zhiyao¹^ORCID,Wang Yong¹^ORCID,Liu Jiao²^ORCID,Sun Guangyong³^ORCID,Tang Ke⁴^ORCID

Affiliation:

1. School of Automation, Central South University, Changsha, China

2. School of Computer Science and Engineering, Nanyang Technological University, Nanyang Avenue, Singapore

3. State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle, Hunan University, Changsha, China

4. Department of Computer Science and Engineering, Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Southern University of Science and Technology, Shenzhen, China

Funder

National Natural Science Foundation of China

Program for Guangdong Introducing Innovative and Entrepreneurial Teams

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221021/10604660/10510462.pdf?arnumber=10510462

Reference44 articles.

1. A fast and elitist multiobjective genetic algorithm: NSGA-II

2. Dynamic Selection Preference-Assisted Constrained Multiobjective Differential Evolution

3. A New Fitness Function With Two Rankings for Evolutionary Constrained Multiobjective Optimization

4. Indicator-Based Constrained Multiobjective Evolutionary Algorithms

5. Cooperative Multiobjective Evolutionary Algorithm With Propulsive Population for Constrained Multiobjective Optimization