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Choice functions for autonomous search in constraint programming: GA vs. PSO [Funkcije izbora za samostalno pretraživanje u ograničenom programiranju: Genetski algoritam nasuprot optimizaciji roja čestica]

dc.contributor.authorSoto R.
dc.contributor.authorCrawford B.
dc.contributor.authorMisra S.
dc.contributor.authorPalma W.
dc.contributor.authorMonfroy E.
dc.contributor.authorCastro C.
dc.contributor.authorParedes F.
dc.date.accessioned2020-09-02T22:28:42Z
dc.date.available2020-09-02T22:28:42Z
dc.date.issued2013
dc.identifier.citation20, 4, 621-627
dc.identifier.issn13303651
dc.identifier.urihttps://hdl.handle.net/20.500.12728/6311
dc.descriptionThe variable and value ordering heuristics are a key element in Constraint Programming. Known together as the enumeration strategy they may have important consequences on the solving process. However, a suitable selection of heuristics is quite hard as their behaviour is complicated to predict. Autonomous search has been recently proposed to handle this concern. The idea is to dynamically replace strategies that exhibit poor performances by more promising ones during the solving process. This replacement is carried out by a choice function, which evaluates a given strategy in a given amount of time via quality indicators. An important phase of this process is performed by an optimizer, which aims at finely tuning the choice function in order to guarantee a precise evaluation of strategies. In this paper we evaluate the performance of two powerful choice functions: the first one supported by a genetic algorithm and the second one by a particle swarm optimizer. We present interesting results and we demonstrate the feasibility of using those optimization techniques for Autonomous Search in a Constraint Programming context.
dc.language.isoen
dc.language.isohr
dc.subjectArtificial intelligence
dc.subjectAutonomous search
dc.subjectConstraint Programming
dc.subjectA-particles
dc.subjectAutonomous searches
dc.subjectChoice function
dc.subjectConstraint programming
dc.subjectKey elements
dc.subjectOptimization techniques
dc.subjectPoor performance
dc.subjectQuality indicators
dc.subjectArtificial intelligence
dc.subjectComputer programming
dc.subjectConstraint theory
dc.subjectFunction evaluation
dc.subjectParticle swarm optimization (PSO)
dc.subjectQuality control
dc.titleChoice functions for autonomous search in constraint programming: GA vs. PSO [Funkcije izbora za samostalno pretraživanje u ograničenom programiranju: Genetski algoritam nasuprot optimizaciji roja čestica]
dc.typeArticle


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