MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework

Blot A, Hoos H, Jourdan L, Marmion M, Trautmann H


Abstract
Automated algorithm configuration procedures play an increasingly important role in the development and application of algorithms for a wide range of computationally challenging problems. Until very recently, these configuration procedures were limited to optimising a single performance objective, such as the running time or solution quality achieved by the algorithm being configured. However, in many applications there is more than one performance objective of interest. This gives rise to the multi-objective automatic algorithm configuration problem, which involves finding a Pareto set of configurations of a given target algorithm that characterises trade-offs between multiple performance objectives. In this work, we introduce MO-ParamILS, a multi-objective extension of the state-of-the-art single-objective algorithm configuration framework ParamILS, and demonstrate that it produces good results on several challenging bi-objective algorithm configuration scenarios compared to a base-line obtained from using a state-of-the-art single-objective algorithm configurator.



Publication type
Conference Paper

Peer reviewed
Yes

Publication status
Accepted

Year
2016

Conference
Learning and Intelligent Optimization, 10th International Conference

Venue
Ischia

Editor
Joaquin Vanschooren et al.

Publisher
Springer International Publishing

Language
English