Artificial Neural Networks Multicriteria Training Based on Graphics Processors

Abstract

The report considers the task of training a multilayer perceptron, formulated as a problem of multiobjective optimization under uncertainty. To solve this problem, the principle of vector minimax was used. A parallel software implementation of a hierarchical evolutionary algorithm for solving a multicriteria optimization problem under uncertainty based on a GPU is presented.

Keywords

• artificial neural network
• multicriteria optimization under uncertainty
• vector minimax
• parallel computing
• GPU