Machine Learning Based Aircraft Recovery Optimization

Abstract

In this research, supervised machine learning is employed to expedite optimization. The core idea is to try to identify components of optimal solutions to new problem instances by leveraging their similarity with alternative (historical) problem instances presented in the offline model-training phase. Our approach prunes the decision space by using machine learning algorithms that are trained using the network- wide optimal decisions for similar scenarios.

Tasks

Reproductions