Non-elitist evolutionary multi-objective optimizers revisited-Reference-Cited by-同舟云学术

Non-elitist evolutionary multi-objective optimizers revisited

Published:2019-07-13 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Genetic and Evolutionary Computation Conference
language:
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Author:

Tanabe Ryoji¹,Ishibuchi Hisao¹

Affiliation:

1. Southern University of Science and Technology

Funder

National Natural Science Foundation of China

The Program for Guangdong Introducing Innovative and Entrepreneurial Teams

The Program for University Key Laboratory of Guangdong Province

Shenzhen Peacock Plan

The Science and Technology Innovation Committee Foundation of Shenzhen

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3321707.3321754

Reference37 articles.

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2. SMS-EMOA: Multiobjective selection based on dominated hypervolume

3. K. Bringmann T. Friedrich and P. Klitzke. 2014. Generic Postprocessing via Subset Selection for Hypervolume and Epsilon-Indicator. In PPSN. 518--527. K. Bringmann T. Friedrich and P. Klitzke. 2014. Generic Postprocessing via Subset Selection for Hypervolume and Epsilon-Indicator. In PPSN. 518--527.

4. D. Brockhoff T. Tran and N. Hansen. 2015. Benchmarking Numerical Multiobjective Optimizers Revisited. In GECCO. 639--646. 10.1145/2739480.2754777 D. Brockhoff T. Tran and N. Hansen. 2015. Benchmarking Numerical Multiobjective Optimizers Revisited. In GECCO. 639--646. 10.1145/2739480.2754777

5. D. Brockhoff T. Tusar D. Tusar T. Wagner N. Hansen and A. Auger. 2016. Biobjective Performance Assessment with the COCO Platform. CoRR abs/1605.01746 (2016). D. Brockhoff T. Tusar D. Tusar T. Wagner N. Hansen and A. Auger. 2016. Biobjective Performance Assessment with the COCO Platform. CoRR abs/1605.01746 (2016).

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