Virtual Savant: learning for optimization

Abstract

This article describes Virtual Savant, a novel paradigm that applies machine learning to derive knowledge from previously-solved optimization problem instances in order to solve new ones in a massively-parallel fashion. Applications of Virtual Savant to two classic combinatorial optimization problems and to one real-world problem are presented and experimental results are discussed.

Tasks

Reproductions