Review of utilization of genetic algorithms in heat transfer problems

By L. Gosselin, Maxime Tye-Gingras, F. Mathieu-Potvin. 2009

430 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/3ea27c186883ceac2248679a6a6114f3f2b88a44

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. Pascal Fua
2. Yash P. Gupta
3. Salim Fettaka
4. Franccois Fleuret
5. Edoardo Remelli
6. Pierre Baqué
7. Jules Thibault

In Computational Theory and Mathematics

1. Pascal Fua
2. Yash P. Gupta
3. Salim Fettaka
4. Franccois Fleuret
5. Pierre Baqué
6. Jules Thibault

In Mechanical Engineering

1. Pascal Fua
2. Yash P. Gupta
3. Salim Fettaka
4. Jules Thibault

Citations in the corpus

• Design of shell-and-tube heat exchangers using multiobjective optimization (2013, background): “A recent review on the application of GAs in heat transfer reported interesting optimization studies on the design of heat exchangers [6].”
• Geodesic Convolutional Shape Optimization (2018, background): “A popular and relatively easy to implement approach to shape optimization relies on genetic algorithms (Gosselin et al., 2009) to explore the space of possible shapes.”