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Design and analysis of diversity-based parent selection schemes for speeding up evolutionary multi-objective optimisation

  • Published:2020-09 Issue: Volume:832 Page:123-142
  • ISSN:0304-3975
  • Container-title:Theoretical Computer Science
  • language:en
  • Short-container-title:Theoretical Computer Science

Author:

Covantes Osuna EdgarORCID,Gao Wanru,Neumann Frank,Sudholt Dirk

Funder

CONACYT

Australian Research Council

European Union Seventh Framework Programme

Publisher

Elsevier BV

Subject

General Computer Science,Theoretical Computer Science

Reference19 articles.

1. A fast and elitist multiobjective genetic algorithm: NSGA-II;Deb;IEEE Trans. Evol. Comput.,2002

2. Multiobjective genetic programming: reducing bloat using SPEA2;Bleuler,2001

3. Indicator-based selection in multiobjective search;Zitzler,2004

4. SMSP-EMOA: augmenting SMS-EMOA with the prospect indicator for multiobjective optimization;Phan,2011

5. On the effect of populations in evolutionary multi-objective optimisation;Giel;Evol. Comput.,2010

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1. Runtime Analysis of Quality Diversity Algorithms;Algorithmica;2024-08-13

2. Hot off the Press: Runtime Analyses of Multi-Objective Evolutionary Algorithms in the Presence of Noise;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2024-07-14

3. Empirical Comparison between MOEAs and Local Search on Multi-Objective Combinatorial Optimisation Problems;Proceedings of the Genetic and Evolutionary Computation Conference;2024-07-14

4. What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms;Proceedings of the Genetic and Evolutionary Computation Conference;2024-07-14

5. Analysis of Multiobjective Evolutionary Algorithms on Fitness Function With Time-Linkage Property;IEEE Transactions on Evolutionary Computation;2024-06
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