A parameterless performance metric for reference-point based multi-objective evolutionary algorithms
Author:
Affiliation:
1. University of Skövde, Sweden
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3321707.3321757
Reference21 articles.
1. The balance between proximity and diversity in multiobjective evolutionary algorithms
2. Consideration of Partial User Preferences in Evolutionary Multiobjective Optimization
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1. An Updated Performance Metric for Preference-Based Evolutionary Multi-Objective Optimization Algorithms;Proceedings of the Genetic and Evolutionary Computation Conference;2024-07-14
2. A surrogate-assisted a priori multiobjective evolutionary algorithm for constrained multiobjective optimization problems;Journal of Global Optimization;2024-05-29
3. A new proximity metric based on optimality conditions for single and multi-objective optimization: Method and validation;Expert Systems with Applications;2024-05
4. 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
5. A Performance Indicator for Interactive Evolutionary Multiobjective Optimization Methods;IEEE Transactions on Evolutionary Computation;2023
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