4 papers
On the performance of deep learning for numerical optimization: an application to protein structure prediction
Hojjat Rakhshani, Lhassane Idoumghar, Soheila Ghambari +2
Deep neural networks have recently drawn considerable attention to build and evaluate artificial learning models for perceptual tasks. Here, we present a study on the performance o…
Bypassing or flying above the obstacles? A novel multi-objective UAV path planning problem
Mahmoud Golabi, Soheila Ghambari, Julien Lepagnot +3
This study proposes a novel multi-objective integer programming model for a collision-free discrete drone path planning problem. Considering the possibility of bypassing obstacles…
From feature selection to continuous optimization
Hojjat Rakhshani, Lhassane Idoumghar, Julien Lepagnot +1
Metaheuristic algorithms (MAs) have seen unprecedented growth thanks to their successful applications in fields including engineering and health sciences. In this work, we investig…
Automatic hyperparameter selection in Autodock
Hojjat Rakhshani, Lhassane Idoumghar, Julien Lepagnot +2
Autodock is a widely used molecular modeling tool which predicts how small molecules bind to a receptor of known 3D structure. The current version of AutoDock uses meta-heuristic a…