Memory based self-adaptive sampling for noisy multi-objective optimization

DOI10.1016/j.ins.2019.09.060zbMath1456.90149OpenAlexW2975021551MaRDI QIDQ1999117

Pratyusha Rakshit

Publication date: 18 March 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2019.09.060

zbMATH Keywords

noisemulti-objective optimizationdifferential evolutionfitness varianceself-adaptive sampling

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29)

Related Items (1)

Cellular Automata, Learning Automata, and Cellular Learning Automata for Optimization

Cites Work

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• Simulated annealing in the presence of noise
• A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 special session on real parameter optimization
• Simulation budget allocation for further enhancing the efficiency of ordinal optimization
• Evolutionary optimisation of noisy multi-objective problems using confidence-based dynamic resampling
• Noise analysis compact differential evolution
• Evolutionary Multi-Criterion Optimization

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