GA performance distributions and randomly generated binary constraint satisfaction problems.

DOI10.1016/S0304-3975(02)00133-0zbMath1061.68182MaRDI QIDQ1853463

B. Naudts, L. Schoofs

Publication date: 21 January 2003

Published in: Theoretical Computer Science (Search for Journal in Brave)

zbMATH Keywords

Genetic algorithmsConstraint satisfaction problemsLandscape analysisPerformance distribution

Mathematics Subject Classification ID

Analysis of algorithms (68W40) Randomized algorithms (68W20)

Related Items (2)

A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training ⋮ A self-adaptive differential evolution algorithm for binary CSPs

Cites Work

• Exploiting the deep structure of constraint problems
• Random constraint satisfaction: A more accurate picture
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