Fast Perturbative Algorithm Configurators

TL;DR

This paper introduces a harmonic mutation operator for perturbative algorithm configurators, achieving faster tuning of single-parameter algorithms in certain landscapes and demonstrating practical improvements over existing methods.

Contribution

It proposes a novel harmonic mutation operator that provably improves tuning efficiency and performs well in practice across various configuration scenarios.

Findings

Harmonic mutation operator tunes single-parameter algorithms in polylogarithmic time.

The operator is nearly as fast as default methods even on worst-case landscapes.

Experimental results show superior performance in multiple configuration scenarios.

Abstract

Recent work has shown that the ParamRLS and ParamILS algorithm configurators can tune some simple randomised search heuristics for standard benchmark functions in linear expected time in the size of the parameter space. In this paper we prove a linear lower bound on the expected time to optimise any parameter tuning problem for ParamRLS, ParamILS as well as for larger classes of algorithm configurators. We propose a harmonic mutation operator for perturbative algorithm configurators that provably tunes single-parameter algorithms in polylogarithmic time for unimodal and approximately unimodal (i.e., non-smooth, rugged with an underlying gradient towards the optimum) parameter spaces. It is suitable as a general-purpose operator since even on worst-case (e.g., deceptive) landscapes it is only by at most a logarithmic factor slower than the default ones used by ParamRLS and ParamILS. An experimental analysis confirms the superiority of the approach in practice for a number of configuration scenarios, including ones involving more than one parameter.