Polynomial genetic programming for response surface modeling. II: Adaptive approximate models with probabilistic optimization problems

DOI10.1007/s00158-004-0461-5zbMath1243.90263OpenAlexW2015436162MaRDI QIDQ438483

J. Herrera, H. S. Yoon

Publication date: 31 July 2012

Published in: Structural and Multidisciplinary Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00158-004-0461-5

zbMATH Keywords

partial interpolation strategy

Mathematics Subject Classification ID

Abstract computational complexity for mathematical programming problems (90C60) Optimization problems in solid mechanics (74P99)

Cites Work

• Polynomial genetic programming for response surface modeling. I. A methodology
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
• On the condition number of covariance matrices in kriging, estimation, and simulation of random fields
• Evolutionary algorithms for single and multicriteria design optimization
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