Archivers for single- and multi-objective evolutionary optimization algorithms
Author:
Affiliation:
1. IIMAS-UNAM, Mexico City, Mexico
2. Cinvestav-IPN, Mexico City, Mexico
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3520304.3534076
Reference7 articles.
1. C. Hernández and O. Schütze . 2022. A Bounded Archive Based for Bi-objective Problems based on Distance and epsilon-dominance to avoid Cyclic Behavior . In GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference. C. Hernández and O. Schütze. 2022. A Bounded Archive Based for Bi-objective Problems based on Distance and epsilon-dominance to avoid Cyclic Behavior. In GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference.
2. Combining Convergence and Diversity in Evolutionary Multiobjective Optimization
3. O. Schütze and C. Hernández. 2021. Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms. Springer. O. Schütze and C. Hernández. 2021. Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms. Springer.
4. Archivers for the representation of the set of approximate solutions for MOPs
5. On the Detection of Nearly Optimal Solutions in the Context of Single-Objective Space Mission Design Problems;Schütze O.;Journal of Aerospace Engineering,2011
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