An enhanced genetic algorithm for structural topology optimization

By Shengyin Wang, Kang Tai, Michael Y. Wang. 2006

169 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computational Theory and Mathematics, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/e9b4c0dd704faf824a59b73588f59aea7a586b9e

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In Civil and Structural Engineering

In Computational Theory and Mathematics

In Mechanics of Materials

Citations in the corpus

Structural Shape and Topology Optimization Using an Implicit Free Boundary Parametrization Method (2006, background): “…as a conceptual design tool has the highest importance in the developing process of all structural optimization methods because of its ability in achieving greatest savings [Rozvany (2001); Bendsøe and Kikuchi (1988); Xie and Steven (1993); Wang, Tai, and Wang (2006); Wang and Wang (2005c)].”
Radial basis functions and level set method for structural topology optimization (2006, background): “It should be noted that the structural topology optimization problems have many solutions such as one global and many local minima [18,73].”
GA topology optimization using random keys for tree encoding of structures (2009, background): “A good description of these various problems is given in Wang et al. (2006) .”
Reducing dimensionality in topology optimization using adaptive design variable fields (2010, methodology): “[6] using a coarse mesh of 24×12 elements.”
A survey of structural and multidisciplinary continuum topology optimization: post 2000 (2014, methodology): “…loading, and geometric dimensions in the topology optimization for minimum compliance (Kharmanda et al. 2004), micro-electromechanical systems (MEMS) (Maute and Frangopol 2003; Wang et al. 2006a), and geometrically nonlinear structures (Jung and Cho 2004) under a probabilistic failure constraint.”
Evolutionary level set method for structural topology optimization (2011, methodology): “In order to improve efficiency in global optimization search for topology of engineering problems, many heuristic algorithms [7,8] have been developed, such as evolutionary algorithm [9,10], genetic algorithms [11,12], ant algorithm and simulated annealing algorithm.”