An adaptive many-objective evolutionary algorithm based on decomposition with two archives and an entropy trigger-Reference-Cited by-同舟云学术

An adaptive many-objective evolutionary algorithm based on decomposition with two archives and an entropy trigger

Published:2023-12-11 Issue: Volume: Page:1-41
ISSN:0305-215X
Container-title:Engineering Optimization
language:en
Short-container-title:Engineering Optimization

Author:

Cao Li¹²³,Wang Maocai¹²,Vasile Massimiliano³,Dai Guangming¹²,Wu Huanqin¹²

Affiliation:

1. School of Computer, China University of Geosciences, Wuhan, People's Republic of China

2. Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, People's Republic of China

3. Department of Mechanical & Aerospace Engineering, University of Strathclyde, Glasgow, UK

Funder

Natural Science Foundation of China

the Joint Funds of Equipment Pre-research and Ministry of Education of China

the 13th Five-year Pre-research Project of Civil Aerospace in China; the Hubei Excellent Young and Middle-aged Science and Technology Innovation Team Plan Project

the Hubei Natural Science Foundation of China

the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education

Publisher

Informa UK Limited

Subject

Applied Mathematics,Industrial and Manufacturing Engineering,Management Science and Operations Research,Control and Optimization,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2023.2283038

Reference67 articles.

1. Aggarwal Charu C. Alexander Hinneburg and Daniel A. Keim. 2001. “On the Surprising Behavior of Distance Metrics in High Dimensional Space.” In Proceedings of the International Conference on Database Theory (ICDT 2001) edited by J. Van den Bussche and V. Vianu. Lecture Notes in Computer Science Vol. 1973 420–434. Berlin: Springer-Verlag. https://doi:org/10.1007/3-540-44503-X_27.

2. A Decomposition-Based Many-Objective Evolutionary Algorithm With Two Types of Adjustments for Direction Vectors

3. Chen Liang Chong Zhou Guangming Dai Yuzhen Zhang and Ruixue Hu. 2016. “Entropy Determined Hybrid Two-Stage Multi-Objective Evolutionary Algorithm Combining Locally Linear Embedding.” In Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC) 2565–2572. Piscataway NJ: IEEE. https://doi.org/10.1109/CEC.2016.7744109.

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

5. A benchmark test suite for evolutionary many-objective optimization

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