On the convergence of the P-algorithm for one-dimensional global optimization of smooth functions

DOI10.1023/A:1022677121193zbMath0985.90075MaRDI QIDQ1807681

James M. Calvin, Antanas Žilinskas

Publication date: 19 December 1999

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

zbMATH Keywords

global optimizationGaussian processes

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Stochastic models in economics (91B70)

Related Items (10)

Univariate global optimization with multiextremal non-differentiable constraints without penalty functions ⋮ P-algorithm based on a simplicial statistical model of multimodal functions ⋮ Global optimization based on a statistical model and simplicial partitioning. ⋮ Stochastic optimization with adaptive restart: a framework for integrated local and global learning ⋮ On the search of the shape parameter in radial basis functions using univariate global optimization methods ⋮ An Adapted Branch and Bound Algorithm for Approximating Real Root of a Ploynomial ⋮ On efficiency of a single variable bi-objective optimization algorithm ⋮ Convex quadratic underestimation and Branch and Bound for univariate global optimization with one nonconvex constraint ⋮ One-dimensional P-algorithm with convergence rate \(O(n^{-3+\delta})\) for smooth functions ⋮ Knapsack problems with sigmoid utilities: approximation algorithms via hybrid optimization

Cites Work

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• Axiomatic characterization of a global optimization algorithm and investigation of its search strategy
• A versatile stochastic model of a function of unknown and time varying form
• Local maxima of Gaussian fields

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