Tuners review: How crucial are set-up values to find effective parameter values?

Elizabeth Montero, María Cristina Riff, Nicolás Rojas-Morales

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

ParamILS, I-Race and Evoca are well-known tuning methods designed to search quality parameter calibrations for metaheuristic algorithms. The set-up of parameter search space can strongly affect the performance of tuning methods. In this work we study how the parameter search definitions affect the quality of parameter calibrations delivered by these tuners. An experimental evaluation using two well known metaheuristic algorithms and a real life case is presented. We also provide some guidelines to consider when defining parameters search spaces according to the tuner used in order to obtain the best performance they can find.

Original languageEnglish
Pages (from-to)108-118
Number of pages11
JournalEngineering Applications of Artificial Intelligence
Volume76
DOIs
Publication statusPublished - 1 Nov 2018

Keywords

  • Parameter search space definition
  • Parameter setting
  • Tuning methods

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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