Designing an Optimal Search Algorithm with Respect to Prior Information

DOI10.1007/978-3-642-33206-7_6zbMath1328.68206OpenAlexW111619230MaRDI QIDQ3459676

Emmanuel Vazquez, Olivier Teytaud

Publication date: 11 January 2016

Published in: Theory and Principled Methods for the Design of Metaheuristics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-33206-7_6

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Uses Software

• AMPL
• CUTEr
• SifDec
• SPACE
• EGO

Cites Work

• An informational approach to the global optimization of expensive-to-evaluate functions
• Continuous lunches are free plus the design of optimal optimization algorithms
• Global optimization of expensive-to-evaluate functions: An empirical comparison of two sampling criteria
• A review of statistical models for global optimization
• Efficient global optimization of expensive black-box functions
• Interpolation of spatial data. Some theory for kriging
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• A taxonomy of global optimization methods based on response surfaces
• Global optimization of stochastic black-box systems via sequential kriging meta-models
• Support Vector Machines
• CUTEr and SifDec
• Global optimization
• A one-dimensional optimization algorithm and its convergence rate under the Wiener measure
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