Evolutionary operators in global optimization with dynamic search trajectories

DOI10.1023/B:NUMA.0000005405.78681.A1zbMath1062.90050OpenAlexW2036596201MaRDI QIDQ1418857

E. C. Laskari, K. E. Parsopoulos, Michael N. Vrahatis

Publication date: 14 January 2004

Published in: Numerical Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/b:numa.0000005405.78681.a1

zbMATH Keywords

global optimizationhybrid methodsnumerical algorithmsdifferential evolutiondynamic search trajectories

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (3)

A numerical study of basins of attraction of zero-finding neural nets designed using control theory ⋮ Dynamic search trajectory methods for global optimization ⋮ A reassessment of the Snyman-Fatti dynamic search trajectory method for unconstrained global optimization

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