Genetic algorithms in computer aided design

By Gábor Renner, Anikó Ekárt. Comput. Aided Des., 2003

544 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/1148107bb21a361c6178aec775410957cd8f84b8

How researchers see this paper

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

In Artificial Intelligence

1. Peter von Buelow
2. Michela Turrin
3. Rudi Stouffs

In Computational Theory and Mathematics

1. Peter von Buelow
2. Michela Turrin
3. Rudi Stouffs

In Mechanical Engineering

1. Peter von Buelow
2. Michela Turrin
3. Rudi Stouffs

Citations in the corpus

• A two-stage stochastic programming model for the optimal design of distributed energy systems (2013, methodology): “Similarly, the master problem in this study is addressed by searching the solution space with genetic algorithm that uses techniques inspired by natural evolution, such as inheritance, crossover and mutation [8,44–46].”
• Design explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms (2011, methodology): “Optimization techniques, such as GAs, can be used to support the design process when conceived as a goal oriented activity, specifically, as a search for a suitable or optimal construction, where a search problem consists of a desired state (goal state), a search space and a search process [78].”