A hybridization approach with predicted solution candidates for improving population-based optimization algorithms

DOI10.1016/j.ins.2021.04.082OpenAlexW3158669091MaRDI QIDQ6065959

Grzegorz Sroka, Mariusz Oszust, Karol Cymerys

Publication date: 11 December 2023

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

Full work available at URL: https://doi.org/10.1016/j.ins.2021.04.082

zbMATH Keywords

global optimizationmeta-heuristicscalibration problemhybridizationinverse regressionpopulation-based algorithms

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (1)

Constants in Markov's and Bernstein inequality on a finite interval in \(\mathbb{R}\)

Cites Work

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• On multivariate minimal polynomials
• The Wind Driven Optimization Technique and its Application in Electromagnetics
• A trust region method based on interior point techniques for nonlinear programming.

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