DeepEMO: A Multi-Indicator Convolutional Neural Network-based Evolutionary Multi-Objective Algorithm
DeepEMO is a multi-indicator multi-objective evolutionary algorithm that uses point cloud classification via a DGCNN model trained with different Pareto fronts.
For further information please contact Emilio Bernal-Zubieta or Jesús Guillermo Falcón-Cardona.
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The authors wish to acknowledge the financial support of the Writing Lab, Institute for the Future of Education, Tecnológico de Monterrey, Mexico, in the production of this work. This work was produced during the Research Internship of Tec Semester thanks to the educational innovation of Tecnológico de Monterrey.