Global optimization using a genetic algorithm with hierarchically structured population

DOI10.1016/j.cam.2013.11.008zbMath1278.90479OpenAlexW2037799084MaRDI QIDQ390485

Mohammad Hasan, H. S. Yoon

Publication date: 8 January 2014

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2013.11.008

zbMATH Keywords

global optimizationgenetic algorithmshierarchical structurecontinuous optimizationpopulation set-based methods

Mathematics Subject Classification ID

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

Related Items (4)

Optimizing termination decision for meta-heuristic search techniques that converge to a static objective-value distribution ⋮ Kinetic-based optimization enhanced by genetic dynamics ⋮ Improved biogeography-based optimization with random ring topology and Powell's method ⋮ A modified quasisecant method for global optimization

Uses Software

• Genocop

Cites Work

• Unnamed Item
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• Particle swarm and ant colony algorithms hybridized for improved continuous optimization
• Integrated crossover rules in real coded genetic algorithms
• Improved particle swarm algorithms for global optimization
• Multi-population genetic algorithm to solve the synchronized and integrated two-level lot sizing and scheduling problem
• A Simplex Method for Function Minimization
• Introduction to global optimization.
• A memetic algorithm for the total tardiness single machine scheduling problem

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