Communities of Minima in Local Optima ...
Document type :
Article dans une revue scientifique
Title :
Communities of Minima in Local Optima Networks of Combinatorial Spaces
Author(s) :
Daolio, Fabio [Auteur]
Tomassini, Marco [Auteur]
Verel, Sébastien [Auteur]
Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Groupe SCOBI
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Ochoa, Gabriela [Auteur]
University of Nottingham, UK [UON]
Tomassini, Marco [Auteur]
Verel, Sébastien [Auteur]
Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Groupe SCOBI
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Ochoa, Gabriela [Auteur]
University of Nottingham, UK [UON]
Journal title :
Physica A: Statistical Mechanics and its Applications
Pages :
1684 - 1694
Publisher :
Elsevier
Publication date :
2011-05
ISSN :
0378-4371
English keyword(s) :
Community structure
Optima networks
Combinatorial fitness landscapes
Optima networks
Combinatorial fitness landscapes
HAL domain(s) :
Informatique [cs]/Intelligence artificielle [cs.AI]
English abstract : [en]
In this work we present a new methodology to study the structure of the configuration spaces of hard combinatorial problems. It consists in building the network that has as nodes the locally optimal configurations and as ...
Show more >In this work we present a new methodology to study the structure of the configuration spaces of hard combinatorial problems. It consists in building the network that has as nodes the locally optimal configurations and as edges the weighted oriented transitions between their basins of attraction. We apply the approach to the detection of communities in the optima networks produced by two different classes of instances of a hard combinatorial optimization problem: the quadratic assignment problem (QAP). We provide evidence indicating that the two problem instance classes give rise to very different configuration spaces. For the so-called real-like class, the networks possess a clear modular structure, while the optima networks belonging to the class of random uniform instances are less well partitionable into clusters. This is convincingly supported by using several statistical tests. Finally, we shortly discuss the consequences of the findings for heuristically searching the corresponding problem spaces.Show less >
Show more >In this work we present a new methodology to study the structure of the configuration spaces of hard combinatorial problems. It consists in building the network that has as nodes the locally optimal configurations and as edges the weighted oriented transitions between their basins of attraction. We apply the approach to the detection of communities in the optima networks produced by two different classes of instances of a hard combinatorial optimization problem: the quadratic assignment problem (QAP). We provide evidence indicating that the two problem instance classes give rise to very different configuration spaces. For the so-called real-like class, the networks possess a clear modular structure, while the optima networks belonging to the class of random uniform instances are less well partitionable into clusters. This is convincingly supported by using several statistical tests. Finally, we shortly 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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