Clustering of Local Optima in Combinatorial ...
Document type :
Communication dans un congrès avec actes
Title :
Clustering of Local Optima in Combinatorial Fitness Landscapes
Author(s) :
Ochoa, Gabriela [Auteur]
Verel, Sébastien [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Groupe SCOBI
Daolio, Fabio [Auteur]
Tomassini, Marco [Auteur]
Verel, Sébastien [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Groupe SCOBI
Daolio, Fabio [Auteur]
Tomassini, Marco [Auteur]
Conference title :
Learning and Intelligent OptimizatioN Conference (LION 5)
City :
Rome
Country :
Italie
Start date of the conference :
2011-01-17
Book title :
LNCS
Publisher :
Springer
Publication date :
2011-02-15
HAL domain(s) :
Informatique [cs]/Intelligence artificielle [cs.AI]
English abstract : [en]
Using the recently proposed model of combinatorial landscapes: local optima networks, we study the distribution of local optima in two classes of instances of the quadratic assignment problem. Our results indicate that the ...
Show more >Using the recently proposed model of combinatorial landscapes: local optima networks, we study the distribution of local optima in two classes of instances of the quadratic assignment problem. Our results indicate that the two problem instance classes give rise to very different configuration spaces. For the so-called real-like class, the optima networks possess a clear modular structure, while the networks belonging to the class of random uniform instances are less well partitionable into clusters. We briefly discuss the consequences of the findings for heuristically searching the corresponding problem spaces.Show less >
Show more >Using the recently proposed model of combinatorial landscapes: local optima networks, we study the distribution of local optima in two classes of instances of the quadratic assignment problem. Our results indicate that the two problem instance classes give rise to very different configuration spaces. For the so-called real-like class, the optima networks possess a clear modular structure, while the networks belonging to the class of random uniform instances are less well partitionable into clusters. We briefly discuss the consequences of the findings for heuristically searching the corresponding problem spaces.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
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