Set Representation and Multi-parent Learning within an Evolutionary Algorithm for Optimal Design of Trusses

DOI10.1007/978-3-540-85068-7_17zbMath1168.68469OpenAlexW1576918845MaRDI QIDQ3539214

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Publication date: 17 November 2008

Published in: Studies in Computational Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-85068-7_17

zbMATH Keywords

evolutionary algorithmtruss designlinkage learningset based representation

Mathematics Subject Classification ID

Nonnumerical algorithms (68W05) Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

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• Linkage learning through probabilistic expression.
• Improved genetic algorithm for design optimization of truss structures with sizing, shape and topology variables
• Steady-state genetic algorithms for discrete optimization of trusses
• Topology optimization of trusses using genetic algorithm, force method and graph theory
• Design of truss structures for minimum weight using genetic algorithms

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