Title :

Local optima networks and the performance of iterated local search

Author(s) :

Daolio, Fabio [Auteur]
Verel, Sébastien [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Groupe SCOBI
Ochoa, Gabriela [Auteur]
Tomassini, Marco [Auteur]

Conference title :

Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference

City :

Philadelphia

Country :

Etats-Unis d'Amérique

Start date of the conference :

2012-07-07

Book title :

Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference

Publisher :

ACM

Publication date :

2012

English keyword(s) :

combinatorial fitness landscape
local optima network
local search heuristics

HAL domain(s) :

Informatique [cs]/Intelligence artificielle [cs.AI]

English abstract : [en]

Local Optima Networks (LONs) have been recently proposed as an alternative model of combinatorial fitness landscapes. The model compresses the information given by the whole search space into a smaller mathematical object ...
Show more >Local Optima Networks (LONs) have been recently proposed as an alternative model of combinatorial fitness landscapes. The model compresses the information given by the whole search space into a smaller mathematical object that is the graph having as vertices the local optima and as edges the possible weighted transitions between them. A new set of metrics can be derived from this model that capture the distribution and connectivity of the local optima in the underlying configuration space. This paper departs from the descriptive analysis of local optima networks, and actively studies the correlation between network features and the performance of a local search heuristic. The NK family of landscapes and the Iterated Local Search metaheuristic are considered. With a statistically-sound approach based on multiple linear regression, it is shown that some LONs' features strongly influence and can even partly predict the performance of a heuristic search algorithm. This study validates the expressive power of LONs as a model of combinatorial fitness landscapes.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL