Theoretical and practical convergence of a self-adaptive penalty algorithm for constrained global optimization

DOI10.1007/s10957-016-1042-7zbMath1373.90145DBLPjournals/jota/CostaFRF17OpenAlexW2561502796WikidataQ57573476 ScholiaQ57573476MaRDI QIDQ1673932

Ana Maria A. C. Rocha, M. Fernanda P. Costa, Edite M. G. P. Fernandes, Rogério B. Francisco

Publication date: 27 October 2017

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

Full work available at URL: http://hdl.handle.net/1822/49143

zbMATH Keywords

global optimizationfirefly algorithmself-adaptive penalty

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Approximation methods and heuristics in mathematical programming (90C59)

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Uses Software

• ABC

Cites Work

• A non-homogeneous firefly algorithm and its convergence analysis
• Heuristic-based firefly algorithm for bound constrained nonlinear binary optimization
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• An approach to constrained global optimization based on exact penalty functions
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• Self-adaptive step firefly algorithm
• Global minimization using an augmented Lagrangian method with variable lower-level constraints
• An artificial fish swarm algorithm based hyperbolic augmented Lagrangian method
• A penalty function-based differential evolution algorithm for constrained global optimization
• A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm
• Memetic particle swarm optimization
• Improved particle swarm algorithms for global optimization
• Firefly penalty-based algorithm for bound constrained mixed-integer nonlinear programming
• Firefly Algorithms for Multimodal Optimization
• Extensions of SUMT for Nonlinear Programming: Equality Constraints and Extrapolation

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