Advances in surrogate based modeling, feasibility analysis, and optimization: A review
By Atharv Bhosekar, Marianthi G. Ierapetritou. Computers and Chemical Engineering, 2018
633 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/a77ac94eab3b0b1472ca64271e2567c39c1c2cfc
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Ponnuthurai Nagaratnam Suganthan
- Francisco Herrera
- Carlos Artemio Coello Coello
- Antonio J. Nebro
- Seyedali Mirjalili
- Daniel Molina
- Javier Del Ser
- Eneko Osaba
In Management Science and Operations Research
- Ponnuthurai Nagaratnam Suganthan
- Daniel Molina
- Carlos Artemio Coello Coello
- Francisco Herrera
- R. Matousek
- Jakub Kudela
- Enrique Herrera-Viedma
- Luis Martínez-López
In Statistics and Probability
- Daniel Molina
- Carlos Artemio Coello Coello
- Ponnuthurai Nagaratnam Suganthan
- Francisco Herrera
- R. Matousek
- Jakub Kudela
Citations in the corpus
- Recent advances and applications of surrogate models for finite element method computations: a review (2022, background): “…structures in a broad range of various industrial applications including aerospace (Yan et al. 2020), automotive (Berthelson et al. 2021), architecture (Westermann and Evins 2019), biomedical engineering (Putra et al. 2018), chemical engineering (Bhosekar and Ierapetritou 2018), and many others.”
- A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems (2021, background): “Regularization approaches have been extensively suggested to deal with this problem, especially with linear models and neural networks [147, 148].”