The impact of using different choice functions when solving CSPs with autonomous search

RICARDO JAVIER SOTO DE GIORGIS, BRODERICK CRAWFORD LABRIN, Rodrigo Olivares, Stefanie Niklander, Eduardo Olguín

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

1 Scopus citations

Abstract

Constraint programming is a powerful technology for the efficient solving of optimization and constraint satisfaction problems (CSPs). A main concern of this technology is that the efficient problem resolution usually relies on the employed solving strategy. Unfortunately, selecting the proper one is known to be complex as the behavior of strategies is commonly unpredictable. Recently, Autonomous Search appeared as a new technique to tackle this concern. The idea is to let the solver adapt its strategy during solving time in order to improve performance. This task is controlled by a choice function which decides, based on performance information, how the strategy must be updated. However, choice functions can be constructed in several manners variating the information used to take decisions. Such variations may certainly conduct to very different resolution processes. In this paper, we study the impact on the solving phase of 16 different carefully constructed choice functions. We employ as test bed a set of well-known benchmarks that collect general features present on most CSPs. Interesting experimental results are obtained in order to provide the best-performing choice functions for solving CSPs.

Original languageEnglish
Title of host publicationTrends in Applied Knowledge-Based Systems and Data Science - 29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, Proceedings
EditorsMoonis Ali, Hamido Fujita, Jun Sasaki, Masaki Kurematsu, Ali Selamat
PublisherSpringer Verlag
Pages904-916
Number of pages13
ISBN (Print)9783319420066
DOIs
StatePublished - 1 Jan 2016
Event29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016 - Morioka, Japan
Duration: 2 Aug 20164 Aug 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9799
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference29th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016
CountryJapan
CityMorioka
Period2/08/164/08/16

Keywords

  • Autonomous search
  • Choice functions
  • Constraint programming
  • Constraint satisfaction
  • Optimization

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