Global optimization using \(q\)-gradients

DOI10.1016/j.ejor.2016.01.001zbMath1346.90679OpenAlexW2237275262MaRDI QIDQ322763

Aline C. Soterroni, Érica J. C. Gouvêa, Marluce C. Scarabello, Rommel G. Regis, Fernando Manuel Ramos

Publication date: 7 October 2016

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2016.01.001

zbMATH Keywords

global optimizationconvergencemetaheuristics\(q\)-calculus\(q\)-gradient vector

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Methods of reduced gradient type (90C52)

Related Items (4)

On \(q\)-BFGS algorithm for unconstrained optimization problems ⋮ On \(q\)-Newton's method for unconstrained multiobjective optimization problems ⋮ A limited memory \(q\)-BFGS algorithm for unconstrained optimization problems ⋮ A \(q\)-Polak-Ribière-Polyak conjugate gradient algorithm for unconstrained optimization problems

Uses Software

• Ipopt
• CMA-ES
• minpack
• OPTI
• CEC 05

Cites Work

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• The q-Gradient Vector for Unconstrained Continuous Optimization Problems
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• Quantum calculus

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