Filter-based stochastic algorithm for global optimization

DOI10.1007/s10898-020-00917-9zbMath1447.90042OpenAlexW3034689853MaRDI QIDQ785632

Ana Maria A. C. Rocha, M. Joseane F. G. Macêdo, M. Fernanda P. Costa, Elizabeth W. Karas

Publication date: 7 August 2020

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1822/66429

zbMATH Keywords

global optimizationfilter methoddynamically dimensioned search

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26)

Related Items (1)

A primal–dual penalty method via rounded weighted-ℓ₁ Lagrangian duality

Uses Software

• DIRECT
• ipfilter
• MLMSRBF

Cites Work

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• Stochastic filter methods for generally constrained global optimization
• A filter-based artificial fish swarm algorithm for constrained global optimization: theoretical and practical issues
• An inexact restoration derivative-free filter method for nonlinear programming
• An SQP-filter method for inequality constrained optimization and its global convergence
• Convergence guarantees for generalized adaptive stochastic search methods for continuous global optimization
• Stochastic radial basis function algorithms for large-scale optimization involving expensive black-box objective and constraint functions
• An electromagnetism-like method for nonlinearly constrained global optimization
• An approach to constrained global optimization based on exact penalty functions
• Filter-based DIRECT method for constrained global optimization
• Augmented Lagrangian methods for nonlinear programming with possible infeasibility
• Unified theory of augmented Lagrangian methods for constrained global optimization
• A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization
• Global convergence of slanting filter methods for nonlinear programming
• A new filter-Levenberg-Marquardt method with disturbance for solving nonlinear complementarity problems
• Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: A survey of the state-of-the-art
• On the global convergence of an SLP-filter algorithm that takes EQP steps
• Algorithmic construction of optimal symmetric Latin hypercube designs.
• Accelerated random search for constrained global optimization assisted by radial basis function surrogates
• A globally convergent primal-dual interior-point filter method for nonlinear programming
• Global minimization using an augmented Lagrangian method with variable lower-level constraints
• A penalty function-based differential evolution algorithm for constrained global optimization
• Global convergence of a general filter algorithm based on an efficiency condition of the step
• Derivative-free filter simulated annealing method for constrained continuous global optimization
• Memetic particle swarm optimization
• A Stochastic Radial Basis Function Method for the Global Optimization of Expensive Functions
• Global convergence of a derivative-free inexact restoration filter algorithm for nonlinear programming
• Handling constraints using multiobjective optimization concepts
• Global Convergence of Filter Methods for Nonlinear Programming
• Hybridizing the electromagnetism-like algorithm with descent search for solving engineering design problems
• A Globally Convergent Filter Method for Nonlinear Programming
• A Pattern Search Filter Method for Nonlinear Programming without Derivatives
• A Multidimensional Filter Algorithm for Nonlinear Equations and Nonlinear Least-Squares
• Global Convergence of a Trust-Region SQP-Filter Algorithm for General Nonlinear Programming
• Benchmarking optimization software with performance profiles.
• Nonlinear programming without a penalty function.

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