Automated, adaptive, and optimized search for CSPs via cuckoo search

Soto R.; Crawford B.; Flores J.; Mella F.; Galleguillos C.; Johnson F.; Paredes F.

dc.contributor.author	Soto R.
dc.contributor.author	Crawford B.
dc.contributor.author	Flores J.
dc.contributor.author	Mella F.
dc.contributor.author	Galleguillos C.
dc.contributor.author	Johnson F.
dc.contributor.author	Paredes F.
dc.date.accessioned	2020-09-02T22:28:40Z
dc.date.available	2020-09-02T22:28:40Z
dc.date.issued	2015
dc.identifier	10.1007/978-3-319-20466-6_46
dc.identifier.citation	9140, , 436-447
dc.identifier.issn	03029743
dc.identifier.uri	https://hdl.handle.net/20.500.12728/6297
dc.description	Constraint Programing is a programming paradigm devoted to the efficient solving of constraint satisfaction problems (CSPs). A CSP is a formal problem representation mainly composed of variables and constraints defining relations among those variables. The resolution process of CSPs is commonly carried out by building and exploring a search tree that holds the possibles solutions. Such a tree is dynamically created by interleaving two different phases: enumeration and propagation. During enumeration, the variables and values are chosen to build the possible solution, while propagation intend to delete the values having no chance to reach a feasible result. Autonomous Search is a new technique that gives the ability to the resolution process to be adaptive by re-configuring its enumeration strategy when poor performances are detected. This technique has exhibited impressive results during the last years. However, such a re-configuration is hard to achieve as parameters are problem-dependent and their best configuration is not stable along the search. In this paper, we introduce an Autonomous Search framework that incorporates a new optimizer based on Cuckoo Search able to efficiently support the re-configuration phase. Our goal is to provide an automated, adaptive, and optimized search system for CSPs. We report encouraging results where our approach clearly improves the performance of previously reported Autonomous Search approaches for CSPs. © Springer International Publishing Switzerland 2015.
dc.language.iso	en
dc.publisher	Springer Verlag
dc.source	Gelbukh A.Tan Y.Das S.Engelbrecht A.Buarque F.Shi Y.
dc.subject	Autonomous search
dc.subject	Constraint programming
dc.subject	Cuckoo search
dc.subject	Nature-inspired algorithms
dc.subject	Swarm-based optimization
dc.subject	Artificial intelligence
dc.subject	Computer programming
dc.subject	Constraint theory
dc.subject	Forestry
dc.subject	Optimization
dc.subject	Autonomous searches
dc.subject	Constraint programming
dc.subject	Cuckoo searches
dc.subject	Defining relations
dc.subject	Nature inspired algorithms
dc.subject	Problem representation
dc.subject	Programming paradigms
dc.subject	Resolution process
dc.subject	Constraint satisfaction problems
dc.title	Automated, adaptive, and optimized search for CSPs via cuckoo search
dc.type	Conference Paper