How to Speed-Up the Automated Configuration of Optimization Algorithms

Abstract

This paper presents a set of capping methods to speed-up the automated configuration of optimization algorithms. These methods use known previous executions to compute a performance envelope, which is used to evaluate new executions and early stop those with unsatisfactory performance. Preliminary experiments on six scenarios show that the capping methods save up to 78% of the configuration effort, while finding configurations of the same quality.