Hybrid neighborhood and global replacement strategies for multi objective evolutionary algorithm based on decomposition-Reference-Cited by-同舟云学术

Hybrid neighborhood and global replacement strategies for multi objective evolutionary algorithm based on decomposition

Published:2021-03-08 Issue: Volume: Page:
ISSN:1864-5909
Container-title:Evolutionary Intelligence
language:en
Short-container-title:Evol. Intel.

Author:

Chen Xiaoji^ORCID,Wang Haibin,Chu Jiankun,Hai Bin,Wang Zhichao

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Vision and Pattern Recognition,Mathematics (miscellaneous)

Link

http://link.springer.com/content/pdf/10.1007/s12065-021-00582-1.pdf

Reference34 articles.

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3. Deb K, Agrawal S, Pratap A, Meyarivan T (2000) A fast elitist non-dominated sorting genetic algorithm for multiobjective optimization: NSGA-II. Paper presented at conference on parallel problem solving from nature. Springer, pp. 849–858

4. M. Laumanns. (2001) SPEA2: Improving the strength Pareto evolutionary algorithm. Institut of Technische Informatik und Kommunikationsnetze (TIK).

5. Zitzler E, Simon Künzli (2004) Indicator-based selection in multiobjective search. International Conference on Parallel Problem Solving from Nature, Birmingham, UK, Springer, pp. 832–842

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