Archiver effects on the performance of state-of-the-art multi- and many-objective evolutionary algorithms
Author:
Affiliation:
1. Universidade Federal do Rio Grande, RN, Brazil
2. University of Manchester, Manchester, UK
3. Université Libre de Bruxelles, Brussels, Belgium
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3321707.3321789
Reference34 articles.
1. HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization
2. On the Complexity of Computing the Hypervolume Indicator
3. SMS-EMOA: Multiobjective selection based on dominated hypervolume
4. An Empirical Assessment of the Properties of Inverted Generational Distance on Multi- and Many-Objective Optimization
5. A Large-Scale Experimental Evaluation of High-Performing Multi- and Many-Objective Evolutionary Algorithms
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2. On the Unbounded External Archive and Population Size in Preference-based Evolutionary Multi-objective Optimization Using a Reference Point;Proceedings of the Genetic and Evolutionary Computation Conference;2023-07-12
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4. Multi-Objective Archiving;IEEE Transactions on Evolutionary Computation;2023
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