Reference Vector-Assisted Adaptive Model Management for Surrogate-Assisted Many-Objective Optimization-Reference-Cited by-同舟云学术

Reference Vector-Assisted Adaptive Model Management for Surrogate-Assisted Many-Objective Optimization

Published:2022-12 Issue:12 Volume:52 Page:7760-7773
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Liu Qiqi¹^ORCID,Cheng Ran²,Jin Yaochu¹^ORCID,Heiderich Martin³,Rodemann Tobias⁴^ORCID

Affiliation:

1. Department of Computer Science, University of Surrey, Guildford, U.K.

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

3. Department of Advanced Vehicle Technology Research, Honda R&D Europe (Deutschland) GmbH, Offenbach/Main, Germany

4. Department of Optimization and Creativity, Honda Research Institute Europe, Offenbach/Main, Germany

Funder

Alexander von Humboldt Professorship for Artificial Intelligence endowed by the German Federal Ministry of Education and Research

Guangdong Provincial Key Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software

Link

http://xplorestaging.ieee.org/ielx7/6221021/9954241/09754985.pdf?arnumber=9754985

Reference54 articles.

1. Multiobjective test problems with degenerate Pareto fronts;zhen;arXiv 1806 02706,2018

2. A review of multiobjective test problems and a scalable test problem toolkit

3. Solving Many-Objective Optimization Problems via Multistage Evolutionary Search

4. A New Decomposition-Based NSGA-II for Many-Objective Optimization

5. A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization

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