Continuum structural topology design with genetic algorithms

By M. Jakiela, Colin D. Chapman, J. Duda, Adenike Adewuya, Kazuhiro Saitou. 2000

255 citations recorded by the source corpus.

Subfields: Building and Construction, Civil and Structural Engineering

View Paper: https://www.semanticscholar.org/paper/e31d85622b1d8a20d5a77a8fecd941d67e561586

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Shamim Akhtar
2. Michael Y. Wang
3. Shengyin Wang
4. Kang Tai
5. Anupam Saxena

In Civil and Structural Engineering

1. Shengyin Wang
2. Michael Y. Wang
3. Kang Tai
4. Anupam Saxena
5. Shamim Akhtar
6. Andrés Tovar
7. John E. Renaud
8. Neal M. Patel

Citations in the corpus

• An enhanced genetic algorithm for structural topology optimization (2006, methodology): “The advantages of GAs would include not only the global nature of the search process, but also the indifference to system specific information [40], especially the derivative information, the versatility of application [31], the ease with which heuristics can be incorporated in optimization [41], th”
• Evolutionary computation and structural design: A survey of the state-of-the-art (2005, background): “Figure 1, a modified version of a figure presented in [211], shows the three categories of structural optimization for continuum design problems while Figure 2 shows the same categories for discrete problems.”
• Optimality Conditions of the Hybrid Cellular Automata for Structural Optimization (2007, methodology): “This has motivated the implementation of specialized numerical methods such as approximation techniques [7–9], methods of moving asymptotes (MMA) [10], optimality criteria [11–13], genetic algorithms [14,15], the so-called evolutionary structural optimization (ESO) approach [16,17], and cellular aut”
• An isogeometrical approach to structural topology optimization by optimality criteria (2012, methodology): “However, several different methods such as the approximation methods (Schmit and Farsi 1974; Schmit and Miura 1976; Vanderplaats and Salajegheh 1989), CONLIN (Fleury 1989) and the method of moving asymptotes (MMA) (Svanberg 1987), even more heuristic methods such as genetic algorithm (Kane and Schoe”
• Structural topology optimization using a genetic algorithm with a morphological geometric representation scheme (2005, methodology): “A third approach illustrated by Jakiela and his coworkers (Chapman et al. 1994; Chapman and Jakiela 1996; Jakiela et al. 2000 ) and Schoenauer and his coworkers (Schoenauer 1995; Kane and Schoenauer 1996) directly addresses the discrete nature of the problem by treating it with a discrete optimizat”
• Topology design with negative masks using gradient search (2011, methodology): “Some other methods that can yield binary material layouts using stochastic techniques are the sub-division scheme (Hull and Canfield 2006) and those by Chapman (Jakiela et al. 2000).”