A hyperheuristic approach for dynamic enumeration strategy selection in constraint satisfaction

Broderick Crawford, Ricardo Soto, Carlos Castro, Eric Monfroy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

26 Scopus citations

Abstract

In this work we show a framework for guiding the classical constraint programming resolution process. Such a framework allows one to measure the resolution process state in order to perform an "on the fly"replacement of strategies exhibiting poor performances. The replacement is performed depending on a quality rank, which is computed by means of a choice function. The choice function determines the performance of a given strategy in a given amount of time through a set of indicators and control parameters. The goal is to select promising strategies to achieve efficient resolution processes. The main novelty of our approach is that we reconfigure the search based solely on performance data gathered while solving the current problem. We report encouraging results where our combination of strategies outperforms the use of individual strategies.

Original languageEnglish
Title of host publicationNew Challenges on Bioinspired Applications - 4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011, Proceedings
Pages295-304
Number of pages10
EditionPART 2
DOIs
StatePublished - 2011
Event4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011 - La Palma, Canary Islands, Spain
Duration: 30 May 20113 Jun 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6687 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011
Country/TerritorySpain
CityLa Palma, Canary Islands
Period30/05/113/06/11

Keywords

  • Constraint Programming
  • Heuristic Search
  • Reactive Search

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